R/isoform_plots.R
In kvittingseerup/IsoformSwitchAnalyzeR: Identify, Annotate and Visualize Isoform Switches with Functional Consequences from both short- and long-read RNA-seq data
Defines functions
switchPlotIsoUsage
switchPlotIsoExp
switchPlotGeneExp
switchPlot
expressionAnalysisPlot
switchPlotTranscript
Documented in
switchPlot
switchPlotGeneExp
switchPlotIsoExp
switchPlotIsoUsage
switchPlotTranscript
switchPlotTranscript <- function(
### Core arguments
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
### Advanced arguments
rescaleTranscripts = TRUE,
rescaleRoot = 3,
plotXaxis = !rescaleTranscripts,
reverseMinus = TRUE,
ifMultipleIdenticalAnnotation = 'summarize',
annotationImportance = c('signal_peptide','protein_domain','idr'),
plotTopology = TRUE,
IFcutoff = 0.05,
abbreviateLocations = TRUE,
rectHegith = 0.2,
codingWidthFactor = 2,
nrArrows = 20,
arrowSize = 0.2,
optimizeForCombinedPlot = FALSE,
condition1 = NULL,
condition2 = NULL,
dIFcutoff = 0.1,
alphas = c(0.05, 0.001),
localTheme = theme_bw()
) {
### Check input
if (TRUE) {
if (class(switchAnalyzeRlist) != 'switchAnalyzeRlist') {
stop(
'The object supplied to \'switchAnalyzeRlist\' must be a \'switchAnalyzeRlist\''
)
}
# check isoform and gene name input
idInfoCheck <- sum(c(is.null(gene), is.null(isoform_id)))
if (idInfoCheck != 1) {
if (idInfoCheck == 2) {
stop('One of \'gene\' or \'isoform_id\' must be given as input')
}
if (idInfoCheck == 0) {
stop('Only one of \'gene\' or \'isoform_id\' can be supplied')
}
}
if (!is.logical(rescaleTranscripts)) {
stop('The \'transformCoordinats\' argument must be either be TRUE or FALSE')
}
if (!ifMultipleIdenticalAnnotation %in% c('summarize', 'number','ignore')) {
stop(
'the argument \'ifMultipleIdenticalAnnotation\' must be either \'summarize\', \'number\' or \'ignore\' - please see documentation for details'
)
}
okImportance <- c('signal_peptide','protein_domain','idr')
if( ! all( okImportance %in% intersect(okImportance, annotationImportance)) ) {
stop('The \'annotationImportance\' must specify the order of all features annotated and only that')
}
if (optimizeForCombinedPlot) {
if (is.null(condition1) | is.null(condition2)) {
stop(
'When optimizeForCombinedPlot is TRUE, both condition1 and condition2 must also be suppplied'
)
}
}
if( switchAnalyzeRlist$sourceId == 'preDefinedSwitches') {
if(is.null(condition1)) {
condition1 <- switchAnalyzeRlist$isoformFeatures$condition_1[1]
}
if(is.null(condition2)) {
condition2 <- switchAnalyzeRlist$isoformFeatures$condition_2[1]
}
}
if(plotTopology) {
if( ! 'topologyAnalysis' %in% names(switchAnalyzeRlist) ) {
message('Omitting toplogy visualization as it has not been added. You can add this analysis through analyzeDeepTMHMM(). To avoid this message set \"plotTopology=FALSE\"')
plotTopology <- FALSE
}
}
isConditional <- ! is.null(condition1)
hasQuant <- ! all(is.na(switchAnalyzeRlist$isoformFeatures$IF1))
### Don't plot topology if it is not annotated
if(plotTopology) {
plotTopology <- 'topologyAnalysis' %in% names(switchAnalyzeRlist)
}
}
### Check for what annotation are stored in the switchAnalyzeRlist
if (TRUE) {
if (!is.null(switchAnalyzeRlist$orfAnalysis)) {
inclORF <- TRUE
if( ! is.null(switchAnalyzeRlist$orfAnalysis$orf_origin) ) {
if ( any( switchAnalyzeRlist$orfAnalysis$orf_origin == 'not_annotated_yet' )) {
stop('Some ORFs have not been annotated yet. Please return to the analyzeNovelIsoformORF() step and start again.')
}
}
} else {
inclORF <- FALSE
warning(
'ORFs have not to have been annoated. If ORF should be visualized it can be annoated with the \'annotatePTC()\' function'
)
}
if (!is.null(switchAnalyzeRlist$domainAnalysis)) {
inclDomainAnalysis <- TRUE
if (!inclORF) {
warning('Cannot plot annoated protein domians when no ORF are annoated')
inclDomainAnalysis <- FALSE
}
} else {
inclDomainAnalysis <- FALSE
}
if (!is.null(switchAnalyzeRlist$idrAnalysis)) {
inclIdrAnalysis <- TRUE
if (!inclORF) {
warning('Cannot plot annoated IDR when no ORF are annoated')
inclIdrAnalysis <- FALSE
}
} else {
inclIdrAnalysis <- FALSE
}
if (!is.null(switchAnalyzeRlist$signalPeptideAnalysis)) {
inclSignalPAnalysis <- TRUE
if (!inclORF) {
warning('Cannot plot annoated signal peptides when no ORF are annoated')
inclSignalPAnalysis <- FALSE
}
} else {
inclSignalPAnalysis <- FALSE
}
if ('codingPotential' %in%
colnames(switchAnalyzeRlist$isoformFeatures)
) {
inclCodingPotential <- TRUE
} else {
inclCodingPotential <- FALSE
}
if ('PTC' %in% colnames(switchAnalyzeRlist$isoformFeatures)) {
inclPTC <- TRUE
} else {
inclPTC <- FALSE
}
}
### interpret gene and isoform_id input
if (TRUE) {
### Handle gene and isoform_id input
if (!is.null(gene)) {
# Decode gene supplied
if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_id)
) {
gene_id <- gene
isoform_id <- unique(
switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in% gene_id
)]
)
} else if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_name)
) {
gene_id <- unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
tolower(
switchAnalyzeRlist$isoformFeatures$gene_name
) %in% tolower(gene)
)])
if (length(gene_id) > 1) {
stop(
paste(
'The gene supplied covers multiple gene_ids (usually due to gene duplications). Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
isoform_id <-
unique(
switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in%
gene_id
)]
)
} else {
similarGenes <- c(
unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_id
)
)]
),
unique(
switchAnalyzeRlist$isoformFeatures$gene_name[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_name
)
)]
)
)
if (length(similarGenes)) {
stop(
paste(
'The gene supplied is not pressent in the switchAnalyzeRlist. did you mean any of: \'',
paste(similarGenes, collapse = '\', \''),
'\'',
sep = ''
)
)
} else {
stop(
'The gene supplied is not pressent in the switchAnalyzeRlist, please re-check the name and try again.'
)
}
}
if (!length(isoform_id)) {
stop(
'No isoforms annotated to the supplied gene was found. re-check the name and try again.'
)
}
} else {
if (any(
isoform_id %in% switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
if (!all(
isoform_id %in%
switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
notFound <-
setdiff(isoform_id,
switchAnalyzeRlist$isoformFeatures$isoform_id)
warning(
paste(
'\nThe following isoform was not found: \'',
paste(notFound, collapse = '\', \''),
'\'. Only the other isoforms will be used\n',
sep = ''
)
)
}
gene_id <- unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id
)
])
if (length(gene_id) > 1) {
stop(
paste(
'The isoforms supplied covers multiple gene_ids. Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
} else {
stop(
'Non of the supplied isoforms were found in the switchAnalyzeRlist, please re-check the name and try again'
)
}
}
}
### Extract isoform and annotation data
if (TRUE) {
### Extract iso annoation
if(TRUE) {
columnsToExtract <-
c(
'isoform_id',
'gene_id',
'gene_name',
'codingPotential',
'PTC',
'class_code',
'sub_cell_location',
'solubility_status',
'isoform_switch_q_value',
'IF_overall',
'IF1',
'IF2',
'dIF'
)
columnsToExtract <-
na.omit(match(
columnsToExtract,
colnames(switchAnalyzeRlist$isoformFeatures)
))
### Extract the rows corresponding to features of interes
if( isConditional ) {
rowsToExtract <-
which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in% isoform_id &
switchAnalyzeRlist$isoformFeatures$condition_1 == condition1 &
switchAnalyzeRlist$isoformFeatures$condition_2 == condition2
)
} else {
rowsToExtract <-
which(switchAnalyzeRlist$isoformFeatures$isoform_id %in% isoform_id)
}
isoInfo <-
unique(switchAnalyzeRlist$isoformFeatures[
rowsToExtract,
columnsToExtract
])
### Subset to used isoforms
if(hasQuant) {
isoInfo$minIF <- apply(
isoInfo[,na.omit(match(c('IF1','IF2'), colnames(isoInfo)) ),drop=FALSE],
1,
function(x) {
max(x, na.rm = TRUE)
}
)
isoInfo <- isoInfo[which(
isoInfo$minIF >= IFcutoff
),]
if(nrow(isoInfo) == 0) {
stop('No isoforms left after filtering via the "IFcutoff" argument.')
}
isoform_id <- isoInfo$isoform_id
}
if( switchAnalyzeRlist$sourceId == 'preDefinedSwitches' ) {
isoInfo <- isoInfo[which(
!is.na(isoInfo$dIF)
),]
isoform_id <- intersect(
isoform_id, isoInfo$isoform_id
)
}
### Remove if all is annotated as NA
if(!is.null(isoInfo$sub_cell_location)) {
if(all(is.na(isoInfo$sub_cell_location))) {
isoInfo$sub_cell_location <- NULL
}
}
if(!is.null(isoInfo$solubility_status)) {
if(all(is.na(isoInfo$solubility_status))) {
isoInfo$solubility_status <- NULL
}
}
### Extract ORF info
columnsToExtract <-
c('isoform_id', 'orfStartGenomic', 'orfEndGenomic','wasTrimmed', 'trimmedStartGenomic')
columnsToExtract <-
na.omit(match(
columnsToExtract,
colnames(switchAnalyzeRlist$orfAnalysis)
))
rowsToExtract <-
which(switchAnalyzeRlist$orfAnalysis$isoform_id %in% isoform_id)
orfInfo <-
switchAnalyzeRlist$orfAnalysis[rowsToExtract, columnsToExtract]
if(nrow(orfInfo) == 0) {
warning(
paste(
'There might somthing wrong with the switchAnalyzeRlist',
'- there are no ORF annoation matching the isoforms of interest:',
paste(isoform_id, collapse = ', '),
'. These isoforoms will be plotted as non-coding.',
sep=' '
)
)
### Add NAs manually
isoInfo$orfStartGenomic <- NA
isoInfo$orfEndGenomic <- NA
isoInfo$wasTrimmed <- FALSE
isoInfo$trimmedStartGenomic <- NA
} else {
inclTrimmedIsoforms <- FALSE
if( 'wasTrimmed' %in% colnames(orfInfo) ) {
if(any( orfInfo$wasTrimmed, na.rm = TRUE) ) {
inclTrimmedIsoforms <- TRUE
}
}
### Combine
isoInfo <- merge(isoInfo, orfInfo, by = 'isoform_id')
}
if (length(unique(isoInfo$gene_id)) > 1) {
stop(
'The isoforms supplied originates from more than one gene - a feature currently not supported. Please revise accordingly'
)
}
geneName <- paste(unique(isoInfo$gene_name), collapse = ',')
}
### Exon data
if(TRUE) {
exonInfo <-
switchAnalyzeRlist$exons[which(
switchAnalyzeRlist$exons$isoform_id %in% isoform_id
), ]
if (!length(exonInfo)) {
stop(
'It seems like there is no exon information advailable for the gene/transcripts supplied. Please update to the latest version of IsoformSwitchAnalyzeR and try again (re-import the data). If the problem persist contact the developer'
)
}
exonInfoSplit <- split(exonInfo, exonInfo$isoform_id)
chrName <- as.character(seqnames(exonInfo)[1])
}
### ORF data
if(TRUE) {
if (inclORF) {
orfStart <-
lapply(split(isoInfo$orfStartGenomic, isoInfo$isoform_id),
unique)
orfEnd <-
lapply(split(isoInfo$orfEndGenomic, isoInfo$isoform_id),
unique)
} else {
orfStart <- split(rep(NA, length(isoform_id)), isoform_id)
orfEnd <-
split(rep(NA, length(isoform_id)), isoform_id)
}
}
### Transcript type
if(TRUE) {
if (inclCodingPotential) {
isCoding <-
lapply(split(isoInfo$codingPotential, isoInfo$isoform_id),
unique)
}
if (inclPTC) {
isPTC <- lapply(split(isoInfo$PTC, isoInfo$isoform_id), unique)
}
}
### Extract basis annoation data
if(TRUE) {
### Make list with annotation
annotationList <- list()
### Domain data
if (inclDomainAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$domainAnalysis$isoform_id
)) {
DomainAnalysis <-
switchAnalyzeRlist$domainAnalysis[which(
switchAnalyzeRlist$domainAnalysis$isoform_id %in%
isoInfo$isoform_id
), ]
DomainAnalysis$isoform_id <-
factor(DomainAnalysis$isoform_id,
levels = unique(isoInfo$isoform_id))
DomainAnalysis$id <- 1:nrow(DomainAnalysis)
### Annotate structural variants
if( !is.null(DomainAnalysis$domain_isotype_simple)) {
DomainAnalysis$domain_sv <- ifelse(
DomainAnalysis$domain_isotype_simple == 'Reference',
yes = '',
no = ' (Non-ref Isotype)'
)
DomainAnalysis$hmm_name <- paste0(
DomainAnalysis$hmm_name,
DomainAnalysis$domain_sv
)
}
annotationList$protein_domain <- DomainAnalysis[,c('isoform_id','pfamStartGenomic','pfamEndGenomic','hmm_name','id')]
}
}
if (inclIdrAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$idrAnalysis$isoform_id
)) {
idrAnalysis <-
switchAnalyzeRlist$idrAnalysis[which(
switchAnalyzeRlist$idrAnalysis$isoform_id %in%
isoInfo$isoform_id
), ]
idrAnalysis$isoform_id <-
factor(idrAnalysis$isoform_id,
levels = unique(isoInfo$isoform_id))
#idrAnalysis$idrName <- 'IDR'
idrAnalysis$id <- 1:nrow(idrAnalysis)
annotationList$idr <- idrAnalysis[,c('isoform_id','idrStartGenomic','idrEndGenomic','id')]
}
}
if (inclSignalPAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$signalPeptideAnalysis$isoform_id
)) {
signalPanalysis <-
switchAnalyzeRlist$signalPeptideAnalysis[which(
switchAnalyzeRlist$signalPeptideAnalysis$isoform_id %in%
isoInfo$isoform_id
), ]
signalPanalysis$genomicClevageAfter <-
unlist(signalPanalysis$genomicClevageAfter)
### Signal P region
signalPdata <- isoInfo[,c('isoform_id','orfStartGenomic')]
colnames(signalPdata)[2] <- 'spStartGenomic'
signalPdata$spEndGenomic <- signalPanalysis$genomicClevageAfter[match(
signalPdata$isoform_id, signalPanalysis$isoform_id
)]
signalPdata$id <- signalPdata$isoform_id
signalPanalysis$isoform_id <-
factor(signalPanalysis$isoform_id,
levels = unique(isoInfo$isoform_id))
annotationList$signal_peptide <- signalPdata
}
}
if (plotTopology) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$topologyAnalysis$isoform_id
)) {
tolologyAnalysis <-
switchAnalyzeRlist$topologyAnalysis[which(
switchAnalyzeRlist$topologyAnalysis$isoform_id %in%
isoInfo$isoform_id
), ]
tolologyAnalysis$isoform_id <-
factor(tolologyAnalysis$isoform_id,
levels = unique(isoInfo$isoform_id))
tolologyAnalysis$id <- 1:nrow(tolologyAnalysis)
annotationList$topology <- tolologyAnalysis[,c('isoform_id','regionStartGenomic','regionEndGenomic','region_type','id')]
}
}
}
### Domain sites
if(TRUE) {
if (inclDomainAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$domainAnalysis$isoform_id
)) {
domainStart <-
split(
DomainAnalysis$pfamStartGenomic,
DomainAnalysis$isoform_id,
drop = FALSE
)
domainEnd <-
split(DomainAnalysis$pfamEndGenomic,
DomainAnalysis$isoform_id,
drop = FALSE)
domainName <-
split(DomainAnalysis$hmm_name,
DomainAnalysis$isoform_id,
drop = FALSE)
### Handle if there are any none-unique domain names:
if (ifMultipleIdenticalAnnotation == 'number') {
domainName <- lapply(domainName, function(aVec) {
duplicatedIndex <- which(duplicated(aVec))
if (length(duplicatedIndex)) {
aVec[duplicatedIndex] <-
paste(aVec[duplicatedIndex],
1:length(duplicatedIndex),
sep = '.')
}
return(aVec)
})
} else if (ifMultipleIdenticalAnnotation == 'summarize') {
domainName <- lapply(domainName, function(aVec) {
nameTable <- as.data.frame(
table(aVec),
stringsAsFactors = FALSE
)
# only modify those with mutiple instances
nameTable$newName <- nameTable$aVec
modifyIndex <- which(nameTable$Freq > 1)
nameTable$newName[modifyIndex] <-
paste(nameTable$aVec[modifyIndex],
' (x',
nameTable$Freq[modifyIndex],
')',
sep = '')
newVec <-
nameTable$newName[match(aVec, nameTable$aVec)]
})
} else if (ifMultipleIdenticalAnnotation != 'ignore') {
stop(
'An error occured with ifMultipleIdenticalAnnotation - please contact developers with reproducible example'
)
}
} else {
domainStart <- NULL # By setting them to null they are ignore from hereon out
domainEnd <- NULL
}
} else {
domainStart <- NULL # By setting them to null they are ignore from hereon out
domainEnd <- NULL
}
}
### IDR Sites
if(TRUE) {
if (inclIdrAnalysis) {
if(
any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$idrAnalysis$isoform_id
)
) {
idrStart <-
split(
idrAnalysis$idrStartGenomic,
idrAnalysis$isoform_id,
drop = FALSE
)
idrEnd <-
split(idrAnalysis$idrEndGenomic,
idrAnalysis$isoform_id,
drop = FALSE)
idrName <-
split(idrAnalysis$idr_type,
idrAnalysis$isoform_id,
drop = FALSE)
### Handle if there are any none-unique domain names
if(TRUE) {
if (ifMultipleIdenticalAnnotation == 'number') {
idrName <- lapply(idrName, function(aVec) {
duplicatedIndex <- which(duplicated(aVec))
if (length(duplicatedIndex)) {
aVec[duplicatedIndex] <-
paste(aVec[duplicatedIndex],
1:length(duplicatedIndex),
sep = '.')
}
return(aVec)
})
} else if (ifMultipleIdenticalAnnotation == 'summarize') {
idrName <- lapply(idrName, function(aVec) {
nameTable <- as.data.frame(
table(aVec),
stringsAsFactors = FALSE
)
# only modify those with mutiple instances
nameTable$newName <- nameTable$aVec
modifyIndex <- which(nameTable$Freq > 1)
nameTable$newName[modifyIndex] <-
paste(nameTable$aVec[modifyIndex],
' (x',
nameTable$Freq[modifyIndex],
')',
sep = '')
newVec <-
nameTable$newName[match(aVec, nameTable$aVec)]
})
} else if (ifMultipleIdenticalAnnotation != 'ignore') {
stop(
'An error occured with ifMultipleIdenticalAnnotation - please contact developers with reproducible example'
)
}
}
} else {
idrStart <- NULL # By setting them to null they are ignore from hereon out
idrEnd <- NULL
}
} else {
idrStart <- NULL # By setting them to null they are ignore from hereon out
idrEnd <- NULL
}
}
### Signal peptide data
if(TRUE) {
if (inclSignalPAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$signalPeptideAnalysis$isoform_id
)) {
cleaveageAfter <-
split(
signalPanalysis$genomicClevageAfter,
signalPanalysis$isoform_id,
drop = FALSE
)
} else {
cleaveageAfter <-
NULL # By setting them to null they are ignore from hereon out
}
} else {
cleaveageAfter <-
NULL # By setting them to null they are ignore from hereon out
}
}
### Toplogy
if(TRUE) {
if (plotTopology) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$topologyAnalysis$isoform_id
)) {
toplologyStart <-
split(
tolologyAnalysis$regionStartGenomic,
tolologyAnalysis$isoform_id,
drop = FALSE
)
toplologyEnd <-
split(tolologyAnalysis$regionEndGenomic,
tolologyAnalysis$isoform_id,
drop = FALSE)
toplologyType <-
split(tolologyAnalysis$region_type,
tolologyAnalysis$isoform_id,
drop = FALSE)
} else {
toplologyStart <- NULL # By setting them to null they are ignore from hereon out
toplologyEnd <- NULL
# turn of visualization since no data
plotTopology <- FALSE
}
} else {
toplologyStart <- NULL # By setting them to null they are ignore from hereon out
toplologyEnd <- NULL
# turn of visualization since no data
plotTopology <- FALSE
}
}
### Trimmed sites
if(TRUE) {
if( inclTrimmedIsoforms ) {
trimmedInfo <- orfInfo[,c('isoform_id','trimmedStartGenomic','orfEndGenomic')]
trimmedInfo$orfEndGenomic[which(is.na(trimmedInfo$trimmedStartGenomic))] <- NA
trimmedInfo$name <- NA
trimmedStart <-
split(
trimmedInfo$trimmedStartGenomic,
trimmedInfo$isoform_id,
drop = FALSE
)
trimmedEnd <-
split(trimmedInfo$orfEndGenomic,
trimmedInfo$isoform_id,
drop = FALSE)
} else {
trimmedStart <- NULL # By setting them to null they are ignore from hereon out
trimmedEnd <- NULL
}
}
}
### Align and massage regions
if(TRUE) {
### Align everything and annoate each region
if(TRUE) {
### Loop over each transcript and make the data.frame with all the annotation data (this is currently the rate limiting step)
myTranscriptPlotDataList <- list()
for (i in seq(along.with = exonInfoSplit)) {
# extract data
transcriptName <- names(exonInfoSplit)[i]
localExons <- exonInfoSplit[[transcriptName]]
# extract local values of where to cut the transcript
localOrfStart <-
orfStart [[transcriptName]]
localOrfEnd <-
orfEnd [[transcriptName]] + 1
localDomainStart <-
domainStart [[transcriptName]]
localDomainEnd <-
domainEnd [[transcriptName]] + 1
localIdrStart <-
idrStart [[transcriptName]]
localIdrEnd <-
idrEnd [[transcriptName]] + 1
localTopStart <-
toplologyStart[[transcriptName]]
localTopEnd <-
toplologyEnd [[transcriptName]] + 1
localtrimmedStart <-
trimmedStart [[transcriptName]]
localtrimmedEnd <-
trimmedEnd [[transcriptName]] + 1
localPepticeCleaveage <-
cleaveageAfter[[transcriptName]]
myCutValues <-
unique(
c(
localOrfStart,
localOrfEnd,
localDomainStart,
localDomainEnd,
localIdrStart,
localIdrEnd,
localTopStart,
localTopEnd,
localtrimmedStart,
localtrimmedEnd,
localPepticeCleaveage
)
) # NULLs are just removed
# cut the exons into smaller part based on the ORF and domain coordinats (if needed)
if (length(myCutValues) & !is.na(myCutValues[1])) {
localExonsDevided <-
cutGRanges(aGRange = localExons, cutValues = myCutValues)
} else {
localExonsDevided <- localExons[, 0]
}
### Add annotation
## add standard annotation
localExonsDevided$type <- 'utr'
localExonsDevided$Domain <- ' transcript'
localExonsDevided$topology <- 'none'
## modify if needed
# ORF
if(length(localOrfStart)) {
if (!is.na(localOrfStart)) {
coordinatPair <- c(localOrfStart, localOrfEnd)
orfRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$type[queryHits(findOverlaps(
subject = orfRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- 'cds'
}
}
# domain - loop over each domain
if (length(localDomainStart)) {
for (j in 1:length(localDomainStart)) {
coordinatPair <- c(localDomainStart[j], localDomainEnd[j])
if( all( !is.na(coordinatPair)) ) {
domainRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$Domain[queryHits(findOverlaps(
subject = domainRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- domainName[[transcriptName]][j]
}
}
}
# IDR
if (length(localIdrStart)) {
for (j in 1:length(localIdrStart)) {
coordinatPair <- c(localIdrStart[j], localIdrEnd[j])
if( all( !is.na(coordinatPair)) ) {
domainRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$Domain[queryHits(findOverlaps(
subject = domainRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- idrName[[transcriptName]][j]
}
}
}
# signal peptide
if (length(localPepticeCleaveage)) {
coordinatPair <- c(localOrfStart, localPepticeCleaveage)
if( all( !is.na(coordinatPair)) ) {
peptideRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$Domain[queryHits(findOverlaps(
subject = peptideRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- 'Signal Peptide'
}
}
# trimmed
if (length(localtrimmedStart)) {
for (j in 1:length(localtrimmedStart)) {
coordinatPair <- c(localtrimmedStart[j], localtrimmedEnd[j])
if( all( !is.na(coordinatPair)) ) {
domainRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$Domain[queryHits(findOverlaps(
subject = domainRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- 'Not Analyzed'
}
}
}
# topology - loop over each domain
if (length(localTopStart)) {
for (j in 1:length(localTopStart)) {
coordinatPair <- c(localTopStart[j], localTopEnd[j])
if( all( !is.na(coordinatPair)) ) {
domainRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$topology[queryHits(findOverlaps(
subject = domainRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- toplologyType[[transcriptName]][j]
}
}
}
# convert to df
localExonsDf <- as.data.frame(localExonsDevided)
### Massage
localExonsDf$transcript <- transcriptName
### determine transcript type
if (inclCodingPotential) {
localCoding <- isCoding[[transcriptName]]
} else {
### I no prediction default to annotation
if( ! is.na(localOrfStart) ) {
localCoding <- TRUE
} else {
localCoding <- NULL
}
}
if (inclPTC) {
localPTC <- isPTC[[transcriptName]]
} else {
localPTC <- NULL
}
localExonsDf$seqnames <-
determineTranscriptClass(ptc = localPTC , coding = localCoding)
colnames(localExonsDf)[1] <- 'seqnames'
# save
myTranscriptPlotDataList[[transcriptName]] <- localExonsDf
}
myTranscriptPlotData <- do.call(rbind, myTranscriptPlotDataList)
}
# myTranscriptPlotData
### Correct names !!! where Tx Names are changed !!!!
if (TRUE) {
### correct transcript names
# Create name annotation (this can be omitted when ggplots astetics mapping against type works)
nameDF <- data.frame(
oldTxName = unique(myTranscriptPlotData$transcript),
newTxName = unique(myTranscriptPlotData$transcript),
stringsAsFactors = FALSE
)
### Modify if class code is defined
if ('class_code' %in% colnames(isoInfo)) {
nameDF$newTxName <- paste(
nameDF$newTxName,
' (',
isoInfo$class_code[match(nameDF$oldTxName, isoInfo$isoform_id)],
')',
sep = ''
)
}
if ( isConditional ) {
### Interpret direction
isoInfo$direction <- 'Unchanged usage'
isoInfo$direction[which(isoInfo$dIF > dIFcutoff )] <- 'Increased usage'
isoInfo$direction[which(isoInfo$dIF < dIFcutoff * -1)] <- 'Decreased usage'
if( ! optimizeForCombinedPlot ) {
### Add dIF
if( ! all(isoInfo$dIF %in% c(0, Inf, -Inf)) ) {
isoInfo$direction <- paste(
isoInfo$direction,
': dIF =',
formatC(round(isoInfo$dIF, digits = 2),digits = 2, format='f') ,
sep=' '
)
}
### Add q-values
if(any( !is.na(isoInfo$isoform_switch_q_value))) {
if( ! all(isoInfo$isoform_switch_q_value %in% c(1, -Inf)) ) {
isoInfo$sig <- evalSig(isoInfo$isoform_switch_q_value, alphas = alphas)
isoInfo$direction <- startCapitalLetter(
paste0(
isoInfo$direction,
' (',
isoInfo$sig,
')'
)
)
}
}
}
### Make new name
nameDF$newTxName <- paste(
nameDF$newTxName,
'\n(',
isoInfo$direction[match(nameDF$oldTxName, isoInfo$isoform_id)],
')',
sep = ''
)
}
### Modify if sub-cell location is defined
if( 'sub_cell_location' %in% colnames(isoInfo) ) {
matchVec <- match(nameDF$oldTxName, isoInfo$isoform_id)
if(abbreviateLocations) {
isoInfo$sub_cell_location <- sapply(
str_split(isoInfo$sub_cell_location, ','),
function(x) {
x <- gsub(pattern = 'Cell_membrane' , replacement = 'Memb' , x = x)
x <- gsub(pattern = 'Cytoplasm' , replacement = 'Cyto' , x = x)
x <- gsub(pattern = 'Endoplasmic_reticulum', replacement = 'ER' , x = x)
x <- gsub(pattern = 'Extracellular' , replacement = 'ExtCell', x = x)
x <- gsub(pattern = 'Golgi_apparatus' , replacement = 'Golgi' , x = x)
x <- gsub(pattern = 'Lysosome_Vacuole' , replacement = 'Lys' , x = x)
x <- gsub(pattern = 'Mitochondrion' , replacement = 'Mito' , x = x)
x <- gsub(pattern = 'Nucleus' , replacement = 'Nucl' , x = x)
x <- gsub(pattern = 'Peroxisome' , replacement = 'Perox' , x = x)
x <- gsub(pattern = 'Plastid' , replacement = 'Plastid', x = x)
x <- paste(x, collapse = ', ')
return(x)
}
)
}
nameDF$newTxName <- paste0(
nameDF$newTxName,
'\n(Location: ',
isoInfo$sub_cell_location[match(
nameDF$oldTxName,
isoInfo$isoform_id
)],
')'
)
}
### Modify if solubility location is defined
if( 'solubility_status' %in% colnames(isoInfo) ) {
matchVec <- match(nameDF$oldTxName, isoInfo$isoform_id)
nameDF$newTxName <- paste0(
nameDF$newTxName,
'\n(',
gsub('_',' ', isoInfo$solubility_status[match(
nameDF$oldTxName,
isoInfo$isoform_id
)]),
')'
)
}
myTranscriptPlotData$transcript <-
nameDF$newTxName[match(
myTranscriptPlotData$transcript, nameDF$oldTxName
)]
### Factorize order
supposedOrder <-
c('Coding',
'Non-coding',
'NMD Insensitive',
'NMD Sensitive',
'Transcripts')
supposedOrder <-
supposedOrder[which(
supposedOrder %in% myTranscriptPlotData$seqnames
)]
myTranscriptPlotData$seqnames <-
factor(myTranscriptPlotData$seqnames)
newOrder <-
match(levels(myTranscriptPlotData$seqnames),
supposedOrder)
myTranscriptPlotData$seqnames <-
factor(myTranscriptPlotData$seqnames,
levels = levels(myTranscriptPlotData$seqnames)[newOrder])
}
### Rescale coordinats if nessesary
if (rescaleTranscripts) {
# Might as well work with smaller numbers
myTranscriptPlotData[, c('start', 'end')] <-
myTranscriptPlotData[, c('start', 'end')] -
min(myTranscriptPlotData[, c('start', 'end')]) + 1
### create conversion table from origial coordiants to rescaled values
allCoordinats <-
sort(unique(
c(
myTranscriptPlotData$start,
myTranscriptPlotData$end
)
))
myCoordinats <-
data.frame(orgCoordinates = allCoordinats,
newCoordinates = allCoordinats)
for (i in 2:nrow(myCoordinats)) {
orgDistance <-
myCoordinats$orgCoordinates[i] -
myCoordinats$orgCoordinates[i - 1]
newDistance <- max(c(1, round(
orgDistance^(1/rescaleRoot)
)))
difference <- orgDistance - newDistance
myCoordinats$newCoordinates [i:nrow(myCoordinats)] <-
myCoordinats$newCoordinates [i:nrow(myCoordinats)] - difference
}
# replace original values
myTranscriptPlotData$start <-
myCoordinats$newCoordinates[match(
myTranscriptPlotData$start,
table = myCoordinats$orgCoordinates
)]
myTranscriptPlotData$end <-
myCoordinats$newCoordinates[match(
myTranscriptPlotData$end,
table = myCoordinats$orgCoordinates
)]
}
### Revers coordinats if nesseary (and transcript is on minus strand)
invertCoordinats <-
reverseMinus & as.character(exonInfo@strand)[1] == '-' # exonInfo
if (invertCoordinats) {
# extract min coordinat
minCoordinat <- min(myTranscriptPlotData[, c('start', 'end')])
# transpose to
myTranscriptPlotData[, c('start', 'end')] <-
myTranscriptPlotData[, c('start', 'end')] - minCoordinat + 1
# calculate how much to extract
subtractNr <- max(myTranscriptPlotData[, c('start', 'end')])
# calculate new coordinats (by subtracting everthing becomes negative, and abs inverts to postive = evertyhing is inversed)
newCoordinats <-
abs(myTranscriptPlotData[, c('start', 'end')] - subtractNr)
# overwrite old coordinats
myTranscriptPlotData$start <- newCoordinats$start
myTranscriptPlotData$end <- newCoordinats$end
myTranscriptPlotData$strand <- '+'
# transpose back so min coordiant is the same
myTranscriptPlotData[, c('start', 'end')] <-
myTranscriptPlotData[, c('start', 'end')] + minCoordinat
}
### order data
if(TRUE) {
### Order by transcript category and name and add index (index ensures names and transcipts are properly plotted)
myTranscriptPlotData <-
myTranscriptPlotData[order(myTranscriptPlotData$seqnames,
myTranscriptPlotData$transcript,
decreasing = TRUE), ]
myTranscriptPlotData$idNr <-
match(myTranscriptPlotData$transcript ,
unique(myTranscriptPlotData$transcript))
}
}
### Create objects for plot parts
if(TRUE) {
### Create lines for toplogy
if(plotTopology) {
toplogyInfo <-
myTranscriptPlotData %>%
filter(topology %in% c(
'signal',
'outside',
'TMhelix',
'inside'
)) %>%
mutate(
topGroup = 1:dplyr::n(),
Topology = dplyr::case_when(
topology == 'signal' ~ 'Signal Peptide',
topology == 'outside' ~ 'Extracellular',
topology == 'inside' ~ 'Intracellular',
topology == 'TMhelix' ~ 'TM helix',
TRUE ~ 'Something with toplogy assignment went wrong - contact developer'
),
idNr = idNr + rectHegith * codingWidthFactor + rectHegith / 3 #lift them up
) %>%
select(idNr, seqnames, start, end, Topology, topGroup) %>%
tidyr::pivot_longer(cols = c('start','end')) %>%
as.data.frame()
}
### Create coordiants to rectangels
if (TRUE) {
# ### Convert coordiants to rectangels coordinats (for plotting) and order them according to draw order
### calculate rectangle coordinates
myTranscriptPlotData$ymin <- myTranscriptPlotData$start
myTranscriptPlotData$ymax <- myTranscriptPlotData$end
myTranscriptPlotData$xmin <-
myTranscriptPlotData$idNr - rectHegith
myTranscriptPlotData$xmax <-
myTranscriptPlotData$idNr + rectHegith
### Change with of coding regions
codingIndex <- which(myTranscriptPlotData$type == 'cds')
myTranscriptPlotData$xmin[codingIndex] <-
myTranscriptPlotData$idNr[codingIndex] -
(rectHegith * codingWidthFactor)
myTranscriptPlotData$xmax[codingIndex] <-
myTranscriptPlotData$idNr[codingIndex] +
(rectHegith * codingWidthFactor)
### Change order to reflect annotationImportance
if(TRUE) {
### Create vector with supposed ordering
annotNameList <- list(
transcript = ' transcript',
notAnalyzed = "Not Analyzed"
)
if(!is.null(domainStart)) {
annotNameList$protein_domain <- unique(unlist(domainName))
}
if(!is.null(idrStart)) {
annotNameList$idr <- unique(unlist(idrName))
}
if(!is.null(cleaveageAfter)) {
annotNameList$signal_peptide <- 'Signal Peptide'
}
annotNameListOrdered <- unlist( annotNameList[c(
'transcript',
'notAnalyzed',
rev(annotationImportance)
)] )
### Reorder data
myTranscriptPlotData$DomainRanking <- match(myTranscriptPlotData$Domain, annotNameListOrdered)
myTranscriptPlotData <- myTranscriptPlotData[order(
myTranscriptPlotData$DomainRanking,
myTranscriptPlotData$seqnames,
myTranscriptPlotData$transcript,
decreasing = FALSE
),]
}
}
### Create transcript inton lines with arrows
if (TRUE) {
totalLengths <-
diff(range(
c(
myTranscriptPlotData$ymin,
myTranscriptPlotData$ymax
)
))
byFactor <- totalLengths / nrArrows
myTranscriptPlotDataSplit <-
split(myTranscriptPlotData, f = myTranscriptPlotData$idNr)
arrowlineDataCombined <-
do.call(rbind, lapply(myTranscriptPlotDataSplit, function(aDF) {
# aDF <- myTranscriptPlotDataSplit[[1]]
# extract introns (if coordinats are inverted start have the largest coordinat now)
if (invertCoordinats) {
localIntrons <-
data.frame(gaps(IRanges(
start = aDF$end, end = aDF$start
)))
} else {
localIntrons <-
data.frame(gaps(IRanges(
start = aDF$start, end = aDF$end
)))
}
if (nrow(localIntrons)) {
# Determine munber of arrows based on total intronseize compare to all transcript
totalIntronSize <- sum(localIntrons$width)
localNrArrows <-
totalIntronSize / totalLengths * nrArrows
localIntrons$nrArrows <-
floor(localIntrons$width /
sum(localIntrons$width) * localNrArrows)
localIntrons$index <-
seq(along.with = localIntrons$start)
# for each intron make the calculate number of arrows (min 1 arrow pr intron since the seq(+2) will always give two coordiants)
localArrowlineData <-
do.call(rbind, lapply(split(
localIntrons,
f = seq(along.with = localIntrons$start)
), function(localDF) {
# localDF <- localIntrons[1,]
mySeq <-
seq(
min(localDF$start),
max(localDF$end) + 1,
length.out = localDF$nrArrows + 2
)
localArrowlineData <-
data.frame(
seqnames = aDF$seqnames[1],
x = aDF$idNr[1],
y = mySeq[-length(mySeq)] - 1,
yend = mySeq[-1],
nrArrows = localDF$nrArrows
)
return(localArrowlineData)
}))
# reverse arrow direction if transcript is on minus strand (and reverse is off) - nessesary since calculations are done on + strand since IRanges cannot handle negative widths
if (!reverseMinus &
as.character(exonInfo@strand)[1] == '-') {
localArrowlineData <-
data.frame(
seqnames = localArrowlineData$seqnames,
x = localArrowlineData$x,
y = localArrowlineData$yend,
yend = localArrowlineData$y,
nrArrows = localArrowlineData$nrArrows
)
}
return(localArrowlineData)
} else {
localArrowlineData <-
data.frame(
seqnames = aDF$seqnames[1],
x = aDF$idNr[1],
y = NA,
yend = NA,
nrArrows = c(0, 1)
)
return(localArrowlineData)
}
}))
arrowlineDataArrows <-
arrowlineDataCombined[which(arrowlineDataCombined$nrArrows != 0), ]
arrowlineDataLines <-
arrowlineDataCombined[which(arrowlineDataCombined$nrArrows == 0), ]
}
### create data.frame for converting between index id and transcript name
idData <-
unique(myTranscriptPlotData[, c('seqnames', 'transcript', 'idNr')])
### create color code for domains
if(TRUE) {
domainsFound <-
unique(myTranscriptPlotData$Domain [which(
! myTranscriptPlotData$Domain %in% c(' transcript', "Not Analyzed")
)])
### Reorder
domainsFound <- sort(domainsFound)
domainsFound <- domainsFound[c(
which( domainsFound == "Signal Peptide"),
which( domainsFound != "Signal Peptide")
)]
### Get colors
if(TRUE) {
if (length(domainsFound) == 0) {
domainsColor <- NULL
} else if (length(domainsFound) < 3) {
#domainsColor <-
# RColorBrewer::brewer.pal(
# n = 3,
# name = 'Dark2'
# )[2:(length(domainsFound) + 1)]
domainsColor <-
RColorBrewer::brewer.pal(
n = 12,
name = 'Paired'
)[c(2,4,6)[1:length(domainsFound)]]
} else if (length(domainsFound) > 12) {
gg_color_hue <- function(n) {
hues <- seq(15, 375, length = n + 1)
hcl(h = hues,
l = 65,
c = 100)[1:n]
}
domainsColor <- gg_color_hue(length(domainsFound))
} else {
domainsColor <-
RColorBrewer::brewer.pal(n = length(domainsFound), name = 'Paired')
}
}
### Fix order
if( "Not Analyzed" %in% myTranscriptPlotData$Domain ) {
domainsFound <- c(domainsFound, "Not Analyzed")
correspondingColors <- c(
"#161616", # for ' transcript'
domainsColor,
'#595959' # For "not analyzed"
)
### Move "not analyzed" color to its corresponding position
apperanceInData <- sort(unique(myTranscriptPlotData$Domain))
moveToIndex <- which(sort(apperanceInData) == "Not Analyzed")
correspondingColors <- c(
correspondingColors[1:(moveToIndex-1)],
correspondingColors[length(correspondingColors)],
correspondingColors[(moveToIndex):(length(correspondingColors)-1)]
)
} else {
correspondingColors <- c(
"#161616", # for ' transcript'
domainsColor
)
}
}
### Combined plotting
if (optimizeForCombinedPlot) {
### Collect all labels
allLabels <- c(
condition1,
condition2,
unique(domainsFound)
)
if(plotTopology) {
allLabels <- c(
allLabels,
unique(toplogyInfo$Topology)
)
}
### Find length of longest label
analyzeStrandCompositionInWhiteSpaces <-
function(aString) {
# aString <- 'Ab1'
round(sum(sapply(
strsplit(aString, '')[[1]],
function(aCharacter) {
# Test if whitespace
if (aCharacter == ' ') {
return(1)
}
# Test if number
if (!is.na(suppressWarnings(as.integer(aCharacter)))) {
return(2) # whitespace pr number
}
# test symbols
if (aCharacter == '_') {
return(2) # whitespace pr character
}
# test symbols
if (aCharacter == '.') {
return(1) # whitespace pr numbers
}
# test upper
if (aCharacter == toupper(aCharacter)) {
return(2.4) # whitespace pr uppercase
}
# else it is probably lower
return(1.8) # whitespace pr lowercase
})))
}
maxCharacter <-
max(c(
sapply(allLabels, analyzeStrandCompositionInWhiteSpaces) ,
50
))
### Modify names to match length
modifyNames <- function(aVec, extendToLength) {
tmp <- sapply(aVec, function(x) {
currentLength <- analyzeStrandCompositionInWhiteSpaces(x)
whitespacesToAdd <-
round(extendToLength - currentLength - 1)
if (whitespacesToAdd > 0) {
x <-
paste(x, paste(rep(
' ', whitespacesToAdd
), collapse = ''), collapse = '')
}
return(x)
})
names(tmp) <- NULL
return(tmp)
}
### Modify them
domainsFound <- modifyNames(domainsFound, maxCharacter)
modifiedNames <-
data.frame(
org = allLabels,
new = modifyNames(allLabels, maxCharacter),
stringsAsFactors = FALSE
)
indexToModify <-
which(myTranscriptPlotData$Domain != ' transcript')
myTranscriptPlotData$Domain[indexToModify] <-
modifiedNames$new[match(
myTranscriptPlotData$Domain[indexToModify] , modifiedNames$org
)]
if(plotTopology) {
toplogyInfo$Topology <-
modifiedNames$new[match(
toplogyInfo$Topology, modifiedNames$org
)]
}
}
### factorize seqnames for all 3 datasets to ensure correct facetting
if(TRUE) {
myTranscriptPlotData$seqnames <-
factor(myTranscriptPlotData$seqnames, levels = supposedOrder)
arrowlineDataArrows$seqnames <-
factor(arrowlineDataArrows$seqnames, levels = supposedOrder)
arrowlineDataLines$seqnames <-
factor(arrowlineDataLines$seqnames, levels = supposedOrder)
idData$seqnames <-
factor(idData$seqnames, levels = supposedOrder)
if(plotTopology) {
toplogyInfo$seqnames <-
factor(toplogyInfo$seqnames, levels = supposedOrder)
}
}
}
### Build plot
if(TRUE) {
myPlot <- ggplot()
### Introns
if (nrow(arrowlineDataLines)) {
myPlot <-
myPlot + geom_segment(data = arrowlineDataLines, aes(
x = y,
xend = yend,
y = x,
yend = x
))
}
if (nrow(arrowlineDataArrows)) {
myPlot <-
myPlot + geom_segment(
data = arrowlineDataArrows,
aes(
x = y,
xend = yend,
y = x,
yend = x
),
arrow = arrow(length = unit(arrowSize, "cm"))
) # intron arrows
}
### transcripts
if(TRUE) {
myPlot <- myPlot +
geom_rect(
data = myTranscriptPlotData,
aes(
xmin = ymin,
ymin = xmin,
xmax = ymax,
ymax = xmax,
fill = Domain
)
)
### Transcript color and theme
myPlot <- myPlot +
scale_fill_manual(
breaks = c('transcript',domainsFound),
values = correspondingColors,
na.value = '#161616'
) + # Correct domian color code so transcripts are black and not shown
scale_y_continuous(breaks = idData$idNr, labels = idData$transcript) # change index numbers back to names
}
### topology
if(plotTopology) {
nToplogy <- length(unique(toplogyInfo$Topology))
#lineColors <- grDevices::gray.colors(n = nToplogy, start = 0.3, end = 0.8)
lineColors <- c(
'#7DC462',
'#774FA0',
'#0D95D0',
'#E72F52'
)[1:nToplogy]
#lineColors <- RColorBrewer::brewer.pal(
# n = 8,
# name = 'Dark2'
#)[c(8, 4, 1)[1:nToplogy]]
myPlot <-
myPlot +
geom_line(
aes(
x = value,
y = idNr,
group = topGroup,
color = Topology
),
data = toplogyInfo,
linewidth = 3
) +
scale_color_manual(values = lineColors)
}
### Optimize apperance
if(TRUE) {
### style and themes
myPlot <-
myPlot +
localTheme + theme(strip.text.y = element_text(angle = 0)) + # change theme and rotate facette labes (ensures readability even though frew are pressent)
theme(axis.title.y = element_blank()) + # remove y-axis label
theme(strip.background = element_rect(fill = "white", linewidth = 0.5))
# facette against transcript type if nessesary
if (!all(supposedOrder == 'Transcripts')) {
myPlot <-
myPlot + facet_grid(seqnames ~ ., scales = 'free_y', space = 'free')
}
# Modify X axis
if (!plotXaxis) {
# remove axis if rescaled
myPlot <-
myPlot + theme(
axis.line = element_blank(),
axis.text.x = element_blank(),
axis.ticks = element_blank(),
axis.title.x = element_blank()
)
} else {
# add chr name
myPlot <- myPlot + labs(x = chrName)
}
if( ! optimizeForCombinedPlot ) {
if( isConditional ) {
if( any(grepl('^placeholder_1$|^placeholder_2$', c(condition1, condition2)) ) ) {
myPlot <- myPlot + labs(title = paste(
'The isoform switch in',
geneName,
sep = ' '
))
} else {
myPlot <- myPlot + labs(title = paste(
'The isoform switch in',
geneName,
paste0(' (', condition1, ' vs ', condition2,')'),
sep = ' '
))
}
} else {
myPlot <- myPlot + labs(title = paste(
'The isoforms in',
geneName,
sep = ' '
))
}
}
}
}
return(myPlot)
}
expressionAnalysisPlot <- function(
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
condition1 = NULL,
condition2 = NULL,
IFcutoff = 0.05,
addErrorbars = TRUE,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
alphas = c(0.05, 0.001),
extendFactor = 0.05,
logYaxis = FALSE,
optimizeForCombinedPlot = FALSE,
localTheme = theme_bw()
) {
### Check input
if (TRUE) {
# check switchAnalyzeRlist
if (class(switchAnalyzeRlist) != 'switchAnalyzeRlist') {
stop(
'The object supplied to \'switchAnalyzeRlist\' is not a \'switchAnalyzeRlist\''
)
}
if( switchAnalyzeRlist$sourceId == 'preDefinedSwitches' ) {
stop(
paste(
'The switchAnalyzeRlist is made from pre-defined isoform switches',
'which means it is made without defining conditions (as it should be).',
'\nThis also means it cannot used to plot conditional expression -',
'if that is your intention you need to create a new',
'switchAnalyzeRlist with the importRdata() function and start over.',
sep = ' '
)
)
}
# check isoform and gene name input
idInfoCheck <- sum(c(is.null(gene), is.null(isoform_id)))
if (idInfoCheck != 1) {
if (idInfoCheck == 0) {
stop('One of \'gene\' or \'isoform_id\' must be given as input')
}
if (idInfoCheck == 2) {
stop('Only one of \'gene\' or \'isoform_id\' can be supplied')
}
}
if (!is.logical(addErrorbars)) {
stop('The argument given to addErrorbars must be a logical')
}
if (!is.logical(confidenceIntervalErrorbars)) {
stop('The argument given to addErrorbars must be a logical')
}
if (confidenceInterval < 0 | confidenceInterval > 1) {
stop(
'The argument given to confidenceInterval must be a number in the interval [0,1]'
)
}
if (extendFactor < 0 | extendFactor > 1) {
stop('The argument given to extendFactor must be a number in the interval [0,1]')
}
# Sig levels
if (length(alphas) != 2) {
stop('A vector of length 2 must be given to the argument \'alphas\'')
}
if (any(alphas < 0) |
any(alphas > 1)) {
stop('The \'alphas\' parameter must be numeric between 0 and 1 ([0,1]).')
}
if (any(alphas > 0.05)) {
warning(
'Most journals and scientists consider an alpha larger than 0.05 untrustworthy. We therefore recommend using alpha values smaller than or queal to 0.05'
)
}
# chech conditions
if (TRUE) {
### Identify conditions
allConditionPairs <-
unique(switchAnalyzeRlist$isoformFeatures[,c(
'condition_1', 'condition_2'
)])
if (nrow(allConditionPairs) > 1) {
if (missing(condition1) | missing(condition2)) {
stop(
'Both the \'condition1\' and \'condition2\' arguments must be supplied (when there is more than two comparisons)'
)
}
if (is.null(condition1) | is.null(condition2)) {
stop(
'Both the \'condition1\' and \'condition2\' arguments must be supplied (when there is more than two comparisons)'
)
}
if (is.null(switchAnalyzeRlist$conditions)) {
stop(
'Please make sure the switchAnalyzeRlist is properly constructed - it is missing the \'condition\' argument'
)
}
if (!all(
c(condition1, condition2) %in%
switchAnalyzeRlist$conditions$condition
)) {
stop(
paste(
'Both condition arguments must be eith of: \'',
paste(
switchAnalyzeRlist$conditions$condition,
collapse = '\', \''
),
'\'',
sep = ''
)
)
}
if (condition1 == condition2) {
stop(
'The \'condition1\' and \'condition2\' arguments must be different'
)
}
levelsToMatch <- c(condition1, condition2)
conditionsFound <-
apply(allConditionPairs, 1, function(x) {
x[1] == condition1 & x[2] == condition2
})
if (!any(conditionsFound)) {
# the the conditions are not found try revers order
conditionsFound <-
apply(allConditionPairs, 1, function(x) {
x[2] == condition1 & x[1] == condition2
})
# if now found change the order of conditions
if (any(conditionsFound)) {
temp <- condition1
condition1 <- condition2
condition2 <- temp
} else {
stop(
paste(
'The wanted comparison: \'',
condition1,
' vs ',
condition2,
'\' is not in the data - please revise accordingly'
)
)
}
}
} else {
if( is.null(condition1) & is.null(condition2)) {
condition1 <- allConditionPairs$condition_1
condition2 <- allConditionPairs$condition_2
}
levelsToMatch <- c(condition1, condition2)
}
}
}
### Modify input (interpret input)
if (TRUE) {
### Handle gene and isoform_id input
if (!is.null(gene)) {
# Decode gene supplied
if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_id)
) {
gene_id <- gene
isoform_id <-
unique(switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in% gene_id
)])
} else if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_name)
) {
gene_id <-
unique(switchAnalyzeRlist$isoformFeatures$gene_id[which(
tolower(
switchAnalyzeRlist$isoformFeatures$gene_name
) %in% tolower(gene)
)])
if (length(gene_id) > 1) {
stop(
paste(
'The gene supplied covers multiple gene_ids (usually due to gene duplications). Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
isoform_id <-
unique(
switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in%
gene_id
)])
} else {
similarGenes <- c(
unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_id
)
)]
),
unique(
switchAnalyzeRlist$isoformFeatures$gene_name[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_name
)
)]
)
)
if (length(similarGenes)) {
stop(
paste(
'The gene supplied is not pressent in the switchAnalyzeRlist. did you mean any of: \'',
paste(similarGenes, collapse = '\', \''),
'\'',
sep = ''
)
)
} else {
stop(
'The gene supplied is not pressent in the switchAnalyzeRlist, please re-check the name and try again.'
)
}
}
if (!length(isoform_id)) {
stop(
'No isoforms annotated to the supplied gene was found. re-check the name and try again.'
)
}
} else {
if (any(
isoform_id %in%
switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
if ( !all(
isoform_id %in%
switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
notFound <-
setdiff(isoform_id,
switchAnalyzeRlist$isoformFeatures$isoform_id)
warning(
paste(
'\nThe following isoform was not found: \'',
paste(notFound, collapse = '\', \''),
'\'. Only the other isoforms will be used\n',
sep = ''
)
)
}
gene_id <- unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id
)]
)
if (length(gene_id) > 1) {
stop(
paste(
'The isoforms supplied covers multiple gene_ids. Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
} else {
stop(
'Non of the supplied isoforms were found in the switchAnalyzeRlist, please re-check the name and try again'
)
}
}
### Look into number of characters
analyzeStrandCompositionInWhiteSpaces <-
function(aString) {
# aString <- 'Ab1'
round(sum( sapply(
strsplit(aString, '')[[1]],
function(aCharacter) {
# Test if whitespace
if (aCharacter == ' ') {
return(1)
}
# Test if number
if (!is.na(suppressWarnings(as.integer(aCharacter)))) {
return(2) # whitespace pr number
}
# test symbols
if (aCharacter == '_') {
return(2) # whitespace pr character
}
# test symbols
if (aCharacter == '.') {
return(1) # whitespace pr numbers
}
# test upper
if (aCharacter == toupper(aCharacter)) {
return(2.4) # whitespace pr uppercase
}
# else it is probably lower
return(1.8) # whitespace pr lowercase
}
) ))
}
maxNrCharacters <- max(
c(
analyzeStrandCompositionInWhiteSpaces(isoform_id),
analyzeStrandCompositionInWhiteSpaces(condition1),
analyzeStrandCompositionInWhiteSpaces(condition2)
)
)
modifyNames <- function(aVec, extendToLength) {
aVec <- as.character(aVec)
tmp <- sapply(aVec, function(x) {
currentLength <- analyzeStrandCompositionInWhiteSpaces(x)
whitespacesToAdd <-
round(extendToLength - currentLength - 1)
if (whitespacesToAdd > 0) {
x <-
paste(x, paste(rep(
' ', whitespacesToAdd
), collapse = ''), collapse = '')
}
return(x)
})
names(tmp) <- NULL
return(tmp)
}
### mofify theme to rotate x axis labels
localTheme$axis.text.x$angle <- -35
localTheme$axis.text.x$hjust <- 0
localTheme$axis.text.x$vjust <- 1
### Helper function
trimWhiteSpace <- function (x) {
gsub("^\\s+|\\s+$", "", x)
}
### Extract gene name
if( 'gene_name' %in% colnames(switchAnalyzeRlist$isoformFeatures) ) {
gene_name <- switchAnalyzeRlist$isoformFeatures$gene_name[match(
gene_id, switchAnalyzeRlist$isoformFeatures$gene_id
)]
} else {
gene_name <- gene_id
}
}
### Extract and make plots
if (TRUE) {
### Common for all
if (TRUE) {
### Make list to store plots
plotList <- list()
extendFactor <- 1 + extendFactor
# helper function
evalSig <- function(pValue, alphas) {
sapply(pValue, function(x) {
if (is.na(x)) {
return('NA')
} else if (x < min(alphas)) {
sigLevel <- '***'
} else if (x < max(alphas)) {
sigLevel <- '*'
} else {
sigLevel <- 'ns'
}
return(sigLevel)
})
}
### Subset to contributing genes
columnsToExtract <-
c(
'isoform_id',
'condition_1',
'condition_2',
'IF1',
'IF2',
'isoform_switch_q_value'
)
isoformUsage <-
unique(switchAnalyzeRlist$isoformFeatures[which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id &
switchAnalyzeRlist$isoformFeatures$condition_1 ==
condition1 &
switchAnalyzeRlist$isoformFeatures$condition_2 ==
condition2
) , columnsToExtract])
if (nrow(isoformUsage) < 1) {
stop(
'The chosen combination of gene/isoforms and conditions are not annoatated in the switchAnalyzeRlist'
)
}
isoformUsage <-
isoformUsage[which(isoformUsage$IF1 > IFcutoff |
isoformUsage$IF2 > IFcutoff), ]
if (nrow(isoformUsage) < 1) {
stop('No isoforms were left after the \'isoformUsage\' filter was applied')
}
isoform_id <-
intersect(isoform_id, isoformUsage$isoform_id)
# Interesting rows - common for gene and isoforms
rowsToExtract <- which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id &
switchAnalyzeRlist$isoformFeatures$condition_1 ==
condition1 &
switchAnalyzeRlist$isoformFeatures$condition_2 ==
condition2
)
### Condition char
### Extract size of condition lavel
allLabels <- c( condition1, condition2 )
if ('domainAnalysis' %in% names(switchAnalyzeRlist)) {
localDomains <-
switchAnalyzeRlist$domainAnalysis[
which(
switchAnalyzeRlist$domainAnalysis$isoform_id
%in% isoform_id
),
c('isoform_id', 'hmm_name')
]
domianList <-
split(
localDomains$hmm_name,
f = localDomains$isoform_id
)
domainNames <-
unique(unlist(lapply(domianList, function(aVec) {
nameTable <- as.data.frame(
table(aVec), stringsAsFactors = FALSE
)
# only modify those with mutiple instances
nameTable$newName <- nameTable$aVec
modifyIndex <- which(nameTable$Freq > 1)
nameTable$newName[modifyIndex] <-
paste(nameTable$aVec[modifyIndex],
' (x',
nameTable$Freq[modifyIndex],
')',
sep = '')
newVec <-
nameTable$newName[match(aVec, nameTable$aVec)]
return(newVec)
})))
allLabels <- c(allLabels, domainNames)
}
if ('idrAnalysis' %in% names(switchAnalyzeRlist)) {
localIdrs <-
switchAnalyzeRlist$idrAnalysis[
which(
switchAnalyzeRlist$idrAnalysis$isoform_id
%in% isoform_id
),
c('isoform_id', 'idr_type')
]
idrList <-
split(
localIdrs$idr_type,
f = localIdrs$isoform_id
)
idrNames <-
unique(unlist(lapply(idrList, function(aVec) {
nameTable <- as.data.frame(
table(aVec), stringsAsFactors = FALSE
)
# only modify those with mutiple instances
nameTable$newName <- nameTable$aVec
modifyIndex <- which(nameTable$Freq > 1)
nameTable$newName[modifyIndex] <-
paste(nameTable$aVec[modifyIndex],
' (x',
nameTable$Freq[modifyIndex],
')',
sep = '')
newVec <-
nameTable$newName[match(aVec, nameTable$aVec)]
return(newVec)
})))
allLabels <- c(allLabels, idrNames)
}
if ('signalPeptideAnalysis' %in% names(switchAnalyzeRlist)) {
if (any(
isoform_id %in%
switchAnalyzeRlist$signalPeptideAnalysis$isoform_id
)) {
allLabels <- c(allLabels, 'Signal Peptide')
}
}
conditionMaxCharacter <-
max(c(
sapply(
allLabels,
analyzeStrandCompositionInWhiteSpaces
),
50
))
}
# Gene expression
if (TRUE) {
### Extract relevant data
columnsToExtract <-
c(
'condition_1',
'condition_2',
'gene_value_1',
'gene_value_2',
'gene_stderr_1',
'gene_stderr_2',
'gene_q_value'
)
geneExpression <-
as.data.frame(unique(switchAnalyzeRlist$isoformFeatures[
rowsToExtract,
columnsToExtract
]))
if (optimizeForCombinedPlot) {
geneExpression$condition_1 <-
modifyNames(aVec = geneExpression$condition_1,
extendToLength = maxNrCharacters)
geneExpression$condition_2 <-
modifyNames(aVec = geneExpression$condition_2,
extendToLength = maxNrCharacters)
}
### Massage expression
geneExpression1 <-
geneExpression[, c(
'condition_1', 'gene_value_1', 'gene_stderr_1'
)]
geneExpression2 <-
geneExpression[, c(
'condition_2', 'gene_value_2', 'gene_stderr_2'
)]
colnames(geneExpression1) <-
colnames(geneExpression2) <-
c('Condition', 'gene_expression', 'stderr')
geneExpressionCombined <-
rbind(geneExpression1, geneExpression2)
### Calculate CI and extract confidence level
if (addErrorbars) {
# add replicateNumber
repNrs <-
switchAnalyzeRlist$condition[which(
switchAnalyzeRlist$conditions$condition %in%
c(condition1, condition2)
), ]
if (optimizeForCombinedPlot) {
repNrs$condition <-
modifyNames(
repNrs$condition,
extendToLength = maxNrCharacters
)
}
geneExpressionCombined <-
merge(geneExpressionCombined,
repNrs,
by.x = 'Condition',
by.y = 'condition')
# calculate CI
if (confidenceIntervalErrorbars) {
#geneExpressionCombined$CI <- geneExpressionCombined$stderr * qt(confidenceInterval/2 + .5, geneExpressionCombined$nrReplicates-1)
geneExpressionCombined$CI <-
geneExpressionCombined$stderr *
qnorm(confidenceInterval / 2 + .5)
} else {
geneExpressionCombined$CI <- geneExpressionCombined$stderr
}
geneExpressionCombined$CI_up <-
geneExpressionCombined$gene_expression +
geneExpressionCombined$CI
geneExpressionCombined$CI_down <-
sapply(geneExpressionCombined$gene_expression -
geneExpressionCombined$CI, function(x)
max(c(0, x)))
### Evalueate signifiance
sigLevelDF <- data.frame(
sigLevel = evalSig(geneExpression$gene_q_value, alphas),
sigLevelPos = max(
c(
geneExpressionCombined$gene_expression,
geneExpressionCombined$CI_up,
geneExpressionCombined$CI_down
),
na.rm = TRUE
) * (extendFactor),
stringsAsFactors = FALSE
)
if (any(is.na(sigLevelDF$sigLevelPos))) {
sigLevelDF$sigLevelPos[which(
is.na(sigLevelDF$sigLevelPos)
)] <- 0
}
} else {
sigLevelDF <- data.frame(
sigLevel = evalSig(geneExpression$gene_q_value, alphas),
sigLevelPos = max(geneExpressionCombined$gene_expression) *
(extendFactor),
stringsAsFactors = FALSE
)
}
# calculate new y axis
additionFactor <- as.integer(logYaxis)
yMax <-
max(sigLevelDF$sigLevelPos + additionFactor) * 1.1
ymin <- 0 + additionFactor
### Remove NA sig level
sigLevelDF <-
sigLevelDF[which(sigLevelDF$sigLevel != 'NA'), ]
#sigLevelDF$sigLevelPos <- sigLevelDF$sigLevelPos + additionFactor
sigAnnot <- nrow(sigLevelDF) != 0
geneExpressionCombined$Analyis <- 'Gene Expression'
### Add levels
geneExpressionCombined$Condition <- factor(
geneExpressionCombined$Condition,
levels = geneExpressionCombined$Condition[sapply(
levelsToMatch, function(x) {
which(grepl(
paste0('^',x,'$'),
trimWhiteSpace(geneExpressionCombined$Condition)
))[1]
}
)]
)
### Build Plot
g1 <-
ggplot(data = geneExpressionCombined, aes(x = Condition))
if( optimizeForCombinedPlot ) {
g1 <- g1 +
geom_bar(
aes(y = gene_expression + additionFactor, fill = Condition),
stat = "identity",
position = 'dodge'
)
} else {
g1 <- g1 +
geom_bar(
aes(y = gene_expression + additionFactor),
stat = "identity",
position = 'dodge'
)
}
# errorbar
if (addErrorbars) {
g1 <-
g1 + geom_errorbar(
aes(
ymax = CI_up + additionFactor,
ymin = CI_down + additionFactor
),
width = 0.2
)
}
# sig indication
if (sigAnnot) {
g1 <- g1 +
geom_segment(
data = sigLevelDF,
aes(
x = 1,
xend = 2,
y = sigLevelPos + additionFactor,
yend = sigLevelPos + additionFactor
)
) +
geom_text(
data = sigLevelDF,
aes(
x = 1.5,
y = sigLevelPos + additionFactor,
label = sigLevel
),
vjust = -0.2,
size = localTheme$text$size * 0.3
)
}
# add the rest
g1 <- g1 +
localTheme + # modify to rotate labels
theme(strip.background = element_rect(
fill = "white",
size = 0.5)
)
if( optimizeForCombinedPlot ) {
g1 <- g1 +
scale_fill_manual(values = c('darkgrey', '#333333')) +
guides(fill="none")
}
if (logYaxis) {
g1 <- g1 + scale_y_log10() +
coord_cartesian(ylim = c(ymin+1, yMax))
} else {
g1 <- g1 + coord_cartesian(ylim = c(ymin, yMax))
}
if( ! optimizeForCombinedPlot ) {
g1 <- g1 +
labs(x = 'Condition', y = 'Gene Expression', title = paste0('Expression of ', gene_name))
} else {
g1 <- g1 +
facet_wrap( ~ Analyis, ncol = 1) +
labs(x = 'Condition', y = 'Gene Expression')
}
### add to list
plotList[['gene_expression']] <- g1
}
# Isoforms
if (TRUE) {
# Extract relevant data
columnsToExtract <-
c(
'isoform_id',
'condition_1',
'condition_2',
'iso_value_1',
'iso_value_2',
'iso_stderr_1',
'iso_stderr_2',
'iso_q_value'
)
isoExpression <-
unique(switchAnalyzeRlist$isoformFeatures[
rowsToExtract,
columnsToExtract
])
repNrs <- switchAnalyzeRlist$condition
if (optimizeForCombinedPlot) {
# Change isoform ids
isoExpression$isoform_id <-
modifyNames(aVec = isoExpression$isoform_id,
extendToLength = maxNrCharacters)
isoExpression$condition_1 <-
modifyNames(aVec = isoExpression$condition_1,
extendToLength = conditionMaxCharacter)
isoExpression$condition_2 <-
modifyNames(aVec = isoExpression$condition_2,
extendToLength = conditionMaxCharacter)
repNrs$condition <-
modifyNames(aVec = repNrs$condition,
extendToLength = conditionMaxCharacter)
}
### Massage data
isoExpression2 <-
reshape2::melt(
isoExpression[, c(
'isoform_id', 'iso_value_1', 'iso_value_2'
)],
id.vars = 'isoform_id'
)
colnames(isoExpression2)[3] <- 'expression'
isoExpression2$Condition <- isoExpression$condition_1
isoExpression2$Condition[which(
grepl('_2$', isoExpression2$variable)
)] <- isoExpression$condition_2
isoExpression2 <- isoExpression2[, -2]
isoStderr <-
reshape2::melt(
isoExpression[, c(
'isoform_id', 'iso_stderr_1', 'iso_stderr_2'
)],
id.vars = 'isoform_id'
)
colnames(isoStderr)[3] <- 'stderr'
isoStderr$Condition <- isoExpression$condition_1
isoStderr$Condition[which(grepl('_2$', isoStderr$variable))] <-
isoExpression$condition_2
isoStderr <- isoStderr[, -2]
isoExpressionCombined <-
merge(isoExpression2,
isoStderr,
by = c('isoform_id', 'Condition'))
### Add CI
if (addErrorbars) {
isoExpressionCombined <-
merge(isoExpressionCombined,
repNrs,
by.x = 'Condition',
by.y = 'condition')
# calculate CI
if (confidenceIntervalErrorbars) {
#isoExpressionCombined$CI <- isoExpressionCombined$stderr * qt(confidenceInterval/2 + .5, isoExpressionCombined$nrReplicates-1)
isoExpressionCombined$CI <-
isoExpressionCombined$stderr *
qnorm(confidenceInterval / 2 + .5)
} else {
isoExpressionCombined$CI <- isoExpressionCombined$stderr
}
isoExpressionCombined$CI_hi <-
isoExpressionCombined$expression + isoExpressionCombined$CI
isoExpressionCombined$CI_low <-
sapply(
isoExpressionCombined$expression -
isoExpressionCombined$CI,
function(x) {
max(c(0, x))
}
)
}
isoExpressionCombined$Analyis <- 'Isoform Expression'
### prepare significance
sigDF <- isoExpression[, c('isoform_id', 'iso_q_value')]
sigDF$sigEval <- evalSig(sigDF$iso_q_value, alphas)
sigDF2 <-
plyr::ddply(
sigDF,
.variables = 'isoform_id',
.fun = function(aDF) {
correspondingExpData <-
isoExpressionCombined[which(
isoExpressionCombined$isoform_id ==
aDF$isoform_id
), ]
if (addErrorbars) {
aDF$ymax <-
max(
c(
correspondingExpData$expression,
correspondingExpData$expression +
correspondingExpData$CI
),
na.rm = TRUE
)
} else {
aDF$ymax <- max(correspondingExpData$expression)
}
return(aDF)
}
)
sigDF2$ymax <-
sigDF2$ymax + max(sigDF2$ymax) * (extendFactor - 1)
sigDF2$isoform_id <- factor(sigDF2$isoform_id)
sigDF2$idNr <- as.numeric(sigDF2$isoform_id)
if (any(is.na(sigDF2$ymax))) {
sigDF2$ymax[which(is.na(sigDF2$ymax))] <- 0
}
additionFactor <- as.integer(logYaxis)
yMax <- max(sigDF2$ymax + additionFactor) * 1.1
ymin <- 0 + additionFactor
### Remove NA sig level
sigDF2 <- sigDF2[which(!is.na(sigDF2$iso_q_value)), ]
sigAnnot <- nrow(sigDF2) != 0
### Add levels
isoExpressionCombined$Condition <- factor(
isoExpressionCombined$Condition,
levels = isoExpressionCombined$Condition[
sapply(
levelsToMatch,
function(x) {
which(grepl(
paste0('^',x,'$'),
trimWhiteSpace(isoExpressionCombined$Condition)
))[1]
}
)
]
)
### Buil plot
g2 <-
ggplot(data = isoExpressionCombined, aes(x = isoform_id)) +
geom_bar(
aes(y = expression + additionFactor, fill = Condition),
stat = "identity",
position = 'dodge'
)
# errorbar
if (addErrorbars) {
g2 <- g2 +
geom_errorbar(
aes(
ymax = CI_hi + additionFactor,
ymin = CI_low + additionFactor,
group = Condition
),
position = position_dodge(width = 0.9),
width = 0.2
)
}
if (sigAnnot) {
g2 <- g2 +
geom_text(
data = sigDF2,
aes(
y = ymax + additionFactor,
label = sigEval
),
vjust = -0.2,
size = localTheme$text$size * 0.3
) +
geom_segment(
data = sigDF2,
aes(
x = idNr - 0.25,
xend = idNr + 0.25,
y = ymax + additionFactor,
yend = ymax + additionFactor
)
)
}
g2 <- g2 +
scale_fill_manual(values = c('darkgrey', '#333333')) +
labs(x = 'Isoform', y = 'Isoform Expression') +
localTheme + # modify to tilt conditions
theme(strip.background = element_rect(
fill = "white",
size = 0.5
))
if (logYaxis) {
g2 <- g2 + scale_y_log10() +
coord_cartesian(ylim = c(ymin+1, yMax))
} else {
g2 <- g2 + coord_cartesian(ylim = c(ymin, yMax))
}
if( ! optimizeForCombinedPlot ) {
g2 <- g2 + labs(x = 'Isoform', y = 'Isoform Expression', title = paste0('Isoform Expression in ', gene_name))
} else {
g2 <- g2 +
facet_wrap( ~ Analyis, ncol = 1) +
labs(x = 'Isoform', y = 'Isoform Expression')
}
### add to list
plotList[['isoform_expression']] <- g2
}
# Isoform usage
if (TRUE) {
if (optimizeForCombinedPlot) {
isoformUsage$condition_1 <-
modifyNames(aVec = isoformUsage$condition_1,
extendToLength = conditionMaxCharacter)
isoformUsage$condition_2 <-
modifyNames(aVec = isoformUsage$condition_2,
extendToLength = conditionMaxCharacter)
isoformUsage$isoform_id <-
modifyNames(aVec = isoformUsage$isoform_id,
extendToLength = maxNrCharacters)
}
### Massage data
isoformUsage2 <-
reshape2::melt(
isoformUsage[, c('isoform_id', 'IF1', 'IF2')],
id.vars = 'isoform_id'
)
colnames(isoformUsage2)[3] <- 'IF'
isoformUsage2$Condition <- isoformUsage$condition_1
isoformUsage2$Condition[which(
grepl('2$', isoformUsage2$variable)
)] <- isoformUsage$condition_2
isoformUsage2 <- isoformUsage2[, -2]
isoformUsage2$Analyis <- 'Isoform Usage'
### prepare significance
sigDF <-
isoformUsage[, c('isoform_id', 'isoform_switch_q_value')]
sigDF$sigEval <-
evalSig(pValue = sigDF$isoform_switch_q_value,
alphas = alphas)
sigDF2 <-
plyr::ddply(
sigDF,
.variables = 'isoform_id',
.fun = function(aDF) {
correspondingExpData <-
isoformUsage2[which(
isoformUsage2$isoform_id == aDF$isoform_id
), ]
aDF$ymax <- max(correspondingExpData$IF, na.rm = TRUE)
return(aDF)
}
)
sigDF2$ymax <-
sigDF2$ymax + max(sigDF2$ymax) * (extendFactor - 1)
sigDF2$isoform_id <- factor(sigDF2$isoform_id)
sigDF2$idNr <- as.numeric(sigDF2$isoform_id)
### Add levels
isoformUsage2$Condition <- factor(
isoformUsage2$Condition,
levels = isoformUsage2$Condition[
sapply(
levelsToMatch,
function(x){
which(grepl(
paste0('^',x,'$'),
trimWhiteSpace(isoformUsage2$Condition)
))[1]
}
)
]
)
yMax <- max(sigDF2$ymax) * 1.1
### Remove NA sig level
sigDF2 <-
sigDF2[which(!is.na(sigDF2$isoform_switch_q_value)), ]
sigAnnot <- nrow(sigDF2) != 0
### Plot it
g3 <- ggplot(data = isoformUsage2, aes(x = isoform_id)) +
geom_bar(aes(y = IF, fill = Condition),
stat = "identity",
position = 'dodge')
# annot
if (sigAnnot) {
g3 <- g3 +
geom_text(
data = sigDF2,
aes(y = ymax, label = sigEval),
vjust = -0.2,
size = localTheme$text$size * 0.3
) +
geom_segment(data = sigDF2,
aes(
x = idNr - 0.25,
xend = idNr + 0.25,
y = ymax,
yend = ymax
)) +
coord_cartesian(ylim = c(0, yMax))
}
g3 <- g3 +
scale_fill_manual(values = c('darkgrey', '#333333')) +
localTheme + # modify to tilt conditions
theme(strip.background = element_rect(
fill = "white",
size = 0.5)
)
if( ! optimizeForCombinedPlot ) {
g3 <- g3 +
labs(x = 'Isoform', y = 'Isoform Fraction (IF)', title = paste0('Isoform Usage in ', gene_name))
} else {
g3 <- g3 +
facet_wrap( ~ Analyis, ncol = 1) +
labs(x = 'Isoform', y = 'Isoform Fraction (IF)')
}
plotList[['isoform_usage']] <- g3
}
}
### Add isoforms analyzed
plotList$isoformsAnalyzed <- isoform_id
### Return result
return(plotList)
}
switchPlot <- function(
### Core arguments
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
condition1,
condition2,
### Advanced arguments
IFcutoff = 0.05,
dIFcutoff = 0.1,
alphas = c(0.05, 0.001),
rescaleTranscripts = TRUE,
plotTopology = TRUE,
reverseMinus = TRUE,
addErrorbars = TRUE,
logYaxis = FALSE,
localTheme = theme_bw(base_size = 8),
additionalArguments = list()
) {
### Test Input
if (TRUE) {
# check switchAnalyzeRlist
if (class(switchAnalyzeRlist) != 'switchAnalyzeRlist') {
stop(
'The object supplied to \'switchAnalyzeRlist\' is not a \'switchAnalyzeRlist\''
)
}
if( switchAnalyzeRlist$sourceId == 'preDefinedSwitches' ) {
stop(
paste(
'The switchAnalyzeRlist is made from pre-defined isoform switches',
'which means it is made without defining conditions (as it should be).',
'\nTherefore a switchPlot cannot be made. Use switchPlotTranscript() instead.',
sep = ' '
)
)
}
if (all(is.na(
switchAnalyzeRlist$isoformFeatures$gene_switch_q_value
))) {
warning(
'We recomend running the isoform switching analysis before doing the transcript plot. See ?detectIsoformSwitching for more details'
)
}
# check isoform and gene name input
idInfoCheck <- sum(c(is.null(gene), is.null(isoform_id)))
if (idInfoCheck != 1) {
if (idInfoCheck == 0) {
stop('One of \'gene\' or \'isoform_id\' must be given as input')
}
if (idInfoCheck == 2) {
stop('Only one of \'gene\' or \'isoform_id\' can be supplied')
}
}
# chech conditions
if (TRUE) {
### Identify conditions
allConditionPairs <-
unique(switchAnalyzeRlist$isoformFeatures[,c(
'condition_1', 'condition_2'
)])
levelsToMatch <- as.vector(t(allConditionPairs))
if (nrow(allConditionPairs) > 1) {
if (missing(condition1) | missing(condition2)) {
stop(
'Both the \'condition1\' and \'condition2\' arguments must be supplied (when there is more than two comparisons)'
)
}
if (is.null(switchAnalyzeRlist$conditions)) {
stop(
'Please make sure the switchAnalyzeRlist is properly constructed - it is missing the \'condition\' argument'
)
}
if (!all(
c(condition1, condition2) %in%
switchAnalyzeRlist$conditions$condition
)) {
stop(
paste(
'Both condition arguments must be eith of: \'',
paste(
switchAnalyzeRlist$conditions$condition,
collapse = '\', \''
),
'\'',
sep = ''
)
)
}
if (condition1 == condition2) {
stop(
'The \'condition1\' and \'condition2\' arguments must be different'
)
}
conditionsFound <-
apply(allConditionPairs, 1, function(x) {
x[1] == condition1 & x[2] == condition2
})
if (!any(conditionsFound)) {
# the the conditions are not found try revers order
conditionsFound <-
apply(allConditionPairs, 1, function(x) {
x[2] == condition1 & x[1] == condition2
})
# if now found change the order of conditions
if (any(conditionsFound)) {
temp <- condition1
condition1 <- condition2
condition2 <- temp
} else {
stop(
paste(
'The wanted comparison: \'',
condition1,
' vs ',
condition2,
'\' is not in the data - please revise accordingly'
)
)
}
}
} else {
condition1 <- allConditionPairs$condition_1
condition2 <- allConditionPairs$condition_2
}
levelsToMatch <-
levelsToMatch[which(
levelsToMatch %in% c(condition1, condition2)
)]
}
}
### Parse additional list argument
if (TRUE) {
### Expression plot arguments
if (TRUE) {
## Make list with default values - can be replaced by as.list(args(expressionPlots)) ?
eArgList <- list(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
isoform_id = isoform_id,
condition1 = condition1,
condition2 = condition2,
IFcutoff = IFcutoff,
addErrorbars = addErrorbars,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
#alphas = c(0.05, 0.001),
alphas = alphas,
logYaxis = logYaxis,
extendFactor = 0.05,
localTheme = localTheme
)
### Modify default arguments if nessesary
# subset to only those not already covered by the arguments
additionalArguments2 <-
additionalArguments[which(
names(additionalArguments) %in% c(
'confidenceIntervalErrorbars',
'confidenceInterval',
'alphas',
'extendFactor',
'rescaleRoot'
)
)]
if (length(additionalArguments2) != 0) {
newArgNames <- names(additionalArguments2)
for (i in seq_along(additionalArguments2)) {
eArgList[[newArgNames[i]]] <- additionalArguments2[[i]]
}
}
}
### Transcript plot arguments
if (TRUE) {
## Make list with default values - can be replaced by as.list(args(expressionPlots)) ?
tArgList <- list(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
isoform_id = isoform_id,
rescaleTranscripts = rescaleTranscripts,
plotTopology = plotTopology,
rescaleRoot = 3,
plotXaxis = !rescaleTranscripts,
reverseMinus = reverseMinus,
ifMultipleIdenticalAnnotation = 'summarize',
rectHegith = 0.2,
codingWidthFactor = 2,
nrArrows = 20,
arrowSize = 0.2,
localTheme = localTheme,
plot = TRUE
)
### Modify default arguments if nessesary
# subset to only those not already covered by the arguments
additionalArguments2 <-
additionalArguments[which(
names(additionalArguments) %in% c(
'ifMultipleIdenticalAnnotation',
'rectHegith',
'codingWidthFactor',
'nrArrows',
'arrowSize',
'rescaleRoot'
)
)]
if (length(additionalArguments2) != 0) {
newArgNames <- names(additionalArguments2)
for (i in seq_along(additionalArguments2)) {
tArgList[[newArgNames[i]]] <- additionalArguments2[[i]]
}
}
}
}
### Make subplots - these functions also check the input thoroughly
if (TRUE) {
# expression plots
expressionPlots <- expressionAnalysisPlot(
switchAnalyzeRlist = eArgList$switchAnalyzeRlist,
gene = eArgList$gene,
isoform_id = eArgList$isoform_id,
condition1 = eArgList$condition1,
condition2 = eArgList$condition2,
IFcutoff = eArgList$IFcutoff,
addErrorbars = eArgList$addErrorbars,
confidenceIntervalErrorbars = eArgList$confidenceIntervalErrorbars,
confidenceInterval = eArgList$confidenceInterval,
alphas = eArgList$alphas,
optimizeForCombinedPlot = TRUE,
logYaxis = eArgList$logYaxis,
extendFactor = eArgList$extendFactor,
localTheme = eArgList$localTheme
)
# transcript plots
transcriptPlot <- switchPlotTranscript(
switchAnalyzeRlist = tArgList$switchAnalyzeRlist,
gene = NULL,
# Ensures only isoforms passing IFcutoff are plotted
isoform_id = expressionPlots$isoformsAnalyzed,
# Ensures only isoforms passing IFcutoff are plotted
rescaleTranscripts = tArgList$rescaleTranscripts,
plotTopology = tArgList$plotTopology,
rescaleRoot = tArgList$rescaleRoot,
plotXaxis = tArgList$plotXaxis,
reverseMinus = tArgList$reverseMinus,
ifMultipleIdenticalAnnotation = tArgList$ifMultipleIdenticalAnnotation,
rectHegith = tArgList$rectHegith,
codingWidthFactor = tArgList$codingWidthFactor,
nrArrows = tArgList$nrArrows,
arrowSize = tArgList$arrowSize,
optimizeForCombinedPlot = TRUE,
condition1 = condition1,
condition2 = condition2,
dIFcutoff = dIFcutoff,
IFcutoff = IFcutoff,
localTheme = localTheme
)
}
### Handle gene and isoform_id input
if (TRUE) {
### Handle gene and isoform_id input
if (!is.null(gene)) {
# Decode gene supplied
if (
tolower(gene) %in% tolower(
switchAnalyzeRlist$isoformFeatures$gene_id
)
) {
gene_id <- gene
isoform_id <-
unique(switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in% gene_id
)])
} else if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_name)
) {
gene_id <-
unique(switchAnalyzeRlist$isoformFeatures$gene_id[which(
tolower(
switchAnalyzeRlist$isoformFeatures$gene_name
) %in% tolower(gene)
)])
if (length(gene_id) > 1) {
stop(
paste(
'The gene supplied covers multiple gene_ids (usually due to gene duplications). Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
isoform_id <-
unique(switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in% gene_id
)])
} else {
similarGenes <- c(
unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_id
)
)]
),
unique(
switchAnalyzeRlist$isoformFeatures$gene_name[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_name
)
)]
)
)
if (length(similarGenes)) {
stop(
paste(
'The gene supplied is not pressent in the switchAnalyzeRlist. did you mean any of: \'',
paste(similarGenes, collapse = '\', \''),
'\'',
sep = ''
)
)
} else {
stop(
'The gene supplied is not pressent in the switchAnalyzeRlist, please re-check the name and try again.'
)
}
}
if (!length(isoform_id)) {
stop(
'No isoforms annotated to the supplied gene was found. re-check the name and try again.'
)
}
} else {
if (any(
isoform_id %in% switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
if (! all(isoform_id %in%
switchAnalyzeRlist$isoformFeatures$isoform_id)
) {
notFound <-
setdiff(isoform_id,
switchAnalyzeRlist$isoformFeatures$isoform_id)
warning(
paste(
'\nThe following isoform was not found: \'',
paste(notFound, collapse = '\', \''),
'\'. Only the other isoforms will be used\n',
sep = ''
)
)
}
gene_id <-
unique(switchAnalyzeRlist$isoformFeatures$gene_id[which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id
)])
if (length(gene_id) > 1) {
stop(
paste(
'The isoforms supplied covers multiple gene_ids. Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
} else {
stop(
'Non of the supplied isoforms were found in the switchAnalyzeRlist, please re-check the name and try again'
)
}
}
}
### Subset to isoforms passing IFcutoff filter
isoform_id <-
intersect(isoform_id, expressionPlots$isoformsAnalyzed)
### Extract gene name
indexToAnalyze <-
which(switchAnalyzeRlist$isoformFeatures$isoform_id %in% isoform_id)
geneName <-
paste(
unique(
switchAnalyzeRlist$isoformFeatures$gene_name[indexToAnalyze]
),
collapse = ','
)
if (geneName == 'NA') {
geneName <- 'unannotated gene'
}
### Extract Index with ORF
isoform_id2 <- isoform_id[which(
! is.na( switchAnalyzeRlist$orfAnalysis$orfTransciptStart[match( isoform_id, switchAnalyzeRlist$orfAnalysis$isoform_id)] )
)]
indexToAnalyze2 <-
which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in% isoform_id2
)
### are domains analysed
if (any(
c('domain_identified', 'signal_peptide_identified','idr_identified') %in%
colnames(switchAnalyzeRlist$isoformFeatures)
)) {
anyDomains <-
any(
switchAnalyzeRlist$isoformFeatures$domain_identified[
indexToAnalyze2
] == 'yes'
) |
any(
switchAnalyzeRlist$isoformFeatures$signal_peptide_identified[
indexToAnalyze2
] == 'yes'
) |
any(
switchAnalyzeRlist$isoformFeatures$idr_identified[
indexToAnalyze2
] == 'yes'
)
if (is.na(anyDomains)) {
anyDomains <- FALSE
}
} else {
anyDomains <- FALSE
}
# Title
myTitle <- qplot(1:3, 1, geom = "blank") + theme(
panel.background = element_blank(),
line = element_blank(),
text = element_blank(),
plot.margin = margin(
t = 0,
r = 0,
b = 0,
l = 0,
unit = "cm"
)
) +
annotate(
geom = 'text',
x = 2,
y = 1,
size = localTheme$text$size * 0.6,
fontface = 'bold',
label = paste(
'The isoform switch in ',
geneName ,
' (' ,
condition1,
' vs ',
condition2,
')',
sep = ''
)
)
### Change plot margin
marginSize <- 0.3
expressionPlots2 <-
lapply(expressionPlots, function(x) {
x +
theme(
plot.margin = margin(
t = 0,
r = marginSize,
b = marginSize,
l = marginSize,
unit = "cm"
),
legend.position="none"
)
})
transcriptPlot2 <-
transcriptPlot + theme(
plot.margin = margin(
t = 0,
r = marginSize,
b = marginSize,
l = marginSize,
unit = "cm"
),
legend.position="none"
)
### Extract the legends and modify them to have equally long text strings
if (TRUE) {
### Extract the two legends
g_legend <- function(a.gplot) {
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <-
which(sapply(tmp$grobs, function(x)
x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
### Convert the legneds to ggplot2 via annotation_custom
if (anyDomains) {
tLegend <- g_legend(transcriptPlot)
transcriptLegend <-
qplot(1:10, 1:10, geom = "blank") + theme_bw() + theme(
line = element_blank(),
text = element_blank(),
panel.border = element_blank()
) +
annotation_custom(
tLegend ,
xmin = 0,
xmax = Inf,
ymin = -Inf,
ymax = Inf
) +
theme(
plot.margin = margin(
t = 0,
r = 0.5,
b = 0,
l = 0.5,
unit = "cm"
),
legend.margin = margin(
t = 0,
r = 0,
b = 0,
l = 0,
unit = "cm"
)
)
} else {
transcriptLegend <-
qplot(1:10, 1:10, geom = "blank") + theme_bw() + theme(
line = element_blank(),
text = element_blank(),
panel.border = element_blank()
)
}
eLegend <- g_legend(expressionPlots[[2]])
expressionLegend <-
qplot(1:10, 1:10, geom = "blank") + theme_bw() + theme(
line = element_blank(),
text = element_blank(),
panel.border = element_blank()
) +
annotation_custom(
eLegend ,
xmin = 0,
xmax = Inf,
ymin = 3,
ymax = 10
) +
theme(
plot.margin = margin(
t = 0,
r = 0.5,
b = 0,
l = 0.5,
unit = "cm"
),
legend.margin = margin(
t = 0,
r = 0,
b = 0,
l = 0,
unit = "cm"
)
)
}
### Plot everything together
plotAreaSize <- 10
legendSize <- 3
nColToUse <- plotAreaSize + legendSize
expPlotLast <- nColToUse - legendSize
lastTwoCols <- (nColToUse - legendSize + 1):nColToUse
# set up veiwport
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrow = 16, ncol = nColToUse)))
# print header
print(myTitle, vp = viewport(
layout.pos.row = 1,
layout.pos.col = 1:(nColToUse - legendSize)
))
# transctipt plot
suppressWarnings(print(
transcriptPlot2 + guides(fill = "none"),
vp = viewport(
layout.pos.row = 2:8,
layout.pos.col = 1:expPlotLast
)
))
### Expression legend
print(expressionLegend,
vp = viewport(layout.pos.row = 9:15, layout.pos.col = lastTwoCols))
# expression
print(
expressionPlots2$isoform_usage + guides(fill = "none"),
vp = viewport(
layout.pos.row = 9:15,
layout.pos.col = 7:expPlotLast
)
)
print(
expressionPlots2$isoform_expression + guides(fill = "none"),
vp = viewport(
layout.pos.row = 9:15,
layout.pos.col = 3:6
)
)
print(
expressionPlots2$gene_expression,
vp = viewport(
layout.pos.row = 9:15,
layout.pos.col = 1:2
)
)
# Transcript Legend
print(transcriptLegend,
vp = viewport(layout.pos.row = 2:8, layout.pos.col = lastTwoCols))
}
switchPlotGeneExp <- function(
switchAnalyzeRlist,
gene = NULL,
condition1 = NULL,
condition2 = NULL,
addErrorbars = TRUE,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
alphas = c(0.05, 0.001),
logYaxis = FALSE,
extendFactor = 0.05,
localTheme = theme_bw()
) {
expressionPlots <- expressionAnalysisPlot(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
condition1 = condition1,
condition2 = condition2,
addErrorbars = addErrorbars,
confidenceIntervalErrorbars = confidenceIntervalErrorbars,
confidenceInterval = confidenceInterval,
alphas = alphas,
extendFactor = extendFactor,
logYaxis = logYaxis,
localTheme = localTheme,
optimizeForCombinedPlot = FALSE
)
return(expressionPlots$gene_expression)
}
switchPlotIsoExp <- function(
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
condition1 = NULL,
condition2 = NULL,
IFcutoff = 0.05,
addErrorbars = TRUE,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
alphas = c(0.05, 0.001),
logYaxis = FALSE,
extendFactor = 0.05,
localTheme = theme_bw()
) {
expressionPlots <- expressionAnalysisPlot(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
isoform_id = isoform_id,
condition1 = condition1,
condition2 = condition2,
IFcutoff = IFcutoff,
addErrorbars = addErrorbars,
confidenceIntervalErrorbars = confidenceIntervalErrorbars,
confidenceInterval = confidenceInterval,
alphas = alphas,
extendFactor = extendFactor,
logYaxis = logYaxis,
localTheme = localTheme,
optimizeForCombinedPlot = FALSE
)
return(expressionPlots$isoform_expression)
}
switchPlotIsoUsage <- function(
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
condition1 = NULL,
condition2 = NULL,
IFcutoff = 0.05,
addErrorbars = TRUE,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
alphas = c(0.05, 0.001),
extendFactor = 0.05,
localTheme = theme_bw()
) {
expressionPlots <- expressionAnalysisPlot(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
isoform_id = isoform_id,
condition1 = condition1,
condition2 = condition2,
IFcutoff = IFcutoff,
addErrorbars = addErrorbars,
confidenceIntervalErrorbars = confidenceIntervalErrorbars,
confidenceInterval = confidenceInterval,
alphas = alphas,
extendFactor = extendFactor,
localTheme = localTheme,
optimizeForCombinedPlot = FALSE
)
return(expressionPlots$isoform_usage)
}
kvittingseerup/IsoformSwitchAnalyzeR documentation built on June 28, 2024, 5:41 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions switchPlotIsoUsage switchPlotIsoExp switchPlotGeneExp switchPlot expressionAnalysisPlot switchPlotTranscript
Documented in switchPlot switchPlotGeneExp switchPlotIsoExp switchPlotIsoUsage switchPlotTranscript
switchPlotTranscript <- function(
### Core arguments
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
### Advanced arguments
rescaleTranscripts = TRUE,
rescaleRoot = 3,
plotXaxis = !rescaleTranscripts,
reverseMinus = TRUE,
ifMultipleIdenticalAnnotation = 'summarize',
annotationImportance = c('signal_peptide','protein_domain','idr'),
plotTopology = TRUE,
IFcutoff = 0.05,
abbreviateLocations = TRUE,
rectHegith = 0.2,
codingWidthFactor = 2,
nrArrows = 20,
arrowSize = 0.2,
optimizeForCombinedPlot = FALSE,
condition1 = NULL,
condition2 = NULL,
dIFcutoff = 0.1,
alphas = c(0.05, 0.001),
localTheme = theme_bw()
) {
### Check input
if (TRUE) {
if (class(switchAnalyzeRlist) != 'switchAnalyzeRlist') {
stop(
'The object supplied to \'switchAnalyzeRlist\' must be a \'switchAnalyzeRlist\''
)
}
# check isoform and gene name input
idInfoCheck <- sum(c(is.null(gene), is.null(isoform_id)))
if (idInfoCheck != 1) {
if (idInfoCheck == 2) {
stop('One of \'gene\' or \'isoform_id\' must be given as input')
}
if (idInfoCheck == 0) {
stop('Only one of \'gene\' or \'isoform_id\' can be supplied')
}
}
if (!is.logical(rescaleTranscripts)) {
stop('The \'transformCoordinats\' argument must be either be TRUE or FALSE')
}
if (!ifMultipleIdenticalAnnotation %in% c('summarize', 'number','ignore')) {
stop(
'the argument \'ifMultipleIdenticalAnnotation\' must be either \'summarize\', \'number\' or \'ignore\' - please see documentation for details'
)
}
okImportance <- c('signal_peptide','protein_domain','idr')
if( ! all( okImportance %in% intersect(okImportance, annotationImportance)) ) {
stop('The \'annotationImportance\' must specify the order of all features annotated and only that')
}
if (optimizeForCombinedPlot) {
if (is.null(condition1) | is.null(condition2)) {
stop(
'When optimizeForCombinedPlot is TRUE, both condition1 and condition2 must also be suppplied'
)
}
}
if( switchAnalyzeRlist$sourceId == 'preDefinedSwitches') {
if(is.null(condition1)) {
condition1 <- switchAnalyzeRlist$isoformFeatures$condition_1[1]
}
if(is.null(condition2)) {
condition2 <- switchAnalyzeRlist$isoformFeatures$condition_2[1]
}
}
if(plotTopology) {
if( ! 'topologyAnalysis' %in% names(switchAnalyzeRlist) ) {
message('Omitting toplogy visualization as it has not been added. You can add this analysis through analyzeDeepTMHMM(). To avoid this message set \"plotTopology=FALSE\"')
plotTopology <- FALSE
}
}
isConditional <- ! is.null(condition1)
hasQuant <- ! all(is.na(switchAnalyzeRlist$isoformFeatures$IF1))
### Don't plot topology if it is not annotated
if(plotTopology) {
plotTopology <- 'topologyAnalysis' %in% names(switchAnalyzeRlist)
}
}
### Check for what annotation are stored in the switchAnalyzeRlist
if (TRUE) {
if (!is.null(switchAnalyzeRlist$orfAnalysis)) {
inclORF <- TRUE
if( ! is.null(switchAnalyzeRlist$orfAnalysis$orf_origin) ) {
if ( any( switchAnalyzeRlist$orfAnalysis$orf_origin == 'not_annotated_yet' )) {
stop('Some ORFs have not been annotated yet. Please return to the analyzeNovelIsoformORF() step and start again.')
}
}
} else {
inclORF <- FALSE
warning(
'ORFs have not to have been annoated. If ORF should be visualized it can be annoated with the \'annotatePTC()\' function'
)
}
if (!is.null(switchAnalyzeRlist$domainAnalysis)) {
inclDomainAnalysis <- TRUE
if (!inclORF) {
warning('Cannot plot annoated protein domians when no ORF are annoated')
inclDomainAnalysis <- FALSE
}
} else {
inclDomainAnalysis <- FALSE
}
if (!is.null(switchAnalyzeRlist$idrAnalysis)) {
inclIdrAnalysis <- TRUE
if (!inclORF) {
warning('Cannot plot annoated IDR when no ORF are annoated')
inclIdrAnalysis <- FALSE
}
} else {
inclIdrAnalysis <- FALSE
}
if (!is.null(switchAnalyzeRlist$signalPeptideAnalysis)) {
inclSignalPAnalysis <- TRUE
if (!inclORF) {
warning('Cannot plot annoated signal peptides when no ORF are annoated')
inclSignalPAnalysis <- FALSE
}
} else {
inclSignalPAnalysis <- FALSE
}
if ('codingPotential' %in%
colnames(switchAnalyzeRlist$isoformFeatures)
) {
inclCodingPotential <- TRUE
} else {
inclCodingPotential <- FALSE
}
if ('PTC' %in% colnames(switchAnalyzeRlist$isoformFeatures)) {
inclPTC <- TRUE
} else {
inclPTC <- FALSE
}
}
### interpret gene and isoform_id input
if (TRUE) {
### Handle gene and isoform_id input
if (!is.null(gene)) {
# Decode gene supplied
if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_id)
) {
gene_id <- gene
isoform_id <- unique(
switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in% gene_id
)]
)
} else if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_name)
) {
gene_id <- unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
tolower(
switchAnalyzeRlist$isoformFeatures$gene_name
) %in% tolower(gene)
)])
if (length(gene_id) > 1) {
stop(
paste(
'The gene supplied covers multiple gene_ids (usually due to gene duplications). Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
isoform_id <-
unique(
switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in%
gene_id
)]
)
} else {
similarGenes <- c(
unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_id
)
)]
),
unique(
switchAnalyzeRlist$isoformFeatures$gene_name[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_name
)
)]
)
)
if (length(similarGenes)) {
stop(
paste(
'The gene supplied is not pressent in the switchAnalyzeRlist. did you mean any of: \'',
paste(similarGenes, collapse = '\', \''),
'\'',
sep = ''
)
)
} else {
stop(
'The gene supplied is not pressent in the switchAnalyzeRlist, please re-check the name and try again.'
)
}
}
if (!length(isoform_id)) {
stop(
'No isoforms annotated to the supplied gene was found. re-check the name and try again.'
)
}
} else {
if (any(
isoform_id %in% switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
if (!all(
isoform_id %in%
switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
notFound <-
setdiff(isoform_id,
switchAnalyzeRlist$isoformFeatures$isoform_id)
warning(
paste(
'\nThe following isoform was not found: \'',
paste(notFound, collapse = '\', \''),
'\'. Only the other isoforms will be used\n',
sep = ''
)
)
}
gene_id <- unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id
)
])
if (length(gene_id) > 1) {
stop(
paste(
'The isoforms supplied covers multiple gene_ids. Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
} else {
stop(
'Non of the supplied isoforms were found in the switchAnalyzeRlist, please re-check the name and try again'
)
}
}
}
### Extract isoform and annotation data
if (TRUE) {
### Extract iso annoation
if(TRUE) {
columnsToExtract <-
c(
'isoform_id',
'gene_id',
'gene_name',
'codingPotential',
'PTC',
'class_code',
'sub_cell_location',
'solubility_status',
'isoform_switch_q_value',
'IF_overall',
'IF1',
'IF2',
'dIF'
)
columnsToExtract <-
na.omit(match(
columnsToExtract,
colnames(switchAnalyzeRlist$isoformFeatures)
))
### Extract the rows corresponding to features of interes
if( isConditional ) {
rowsToExtract <-
which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in% isoform_id &
switchAnalyzeRlist$isoformFeatures$condition_1 == condition1 &
switchAnalyzeRlist$isoformFeatures$condition_2 == condition2
)
} else {
rowsToExtract <-
which(switchAnalyzeRlist$isoformFeatures$isoform_id %in% isoform_id)
}
isoInfo <-
unique(switchAnalyzeRlist$isoformFeatures[
rowsToExtract,
columnsToExtract
])
### Subset to used isoforms
if(hasQuant) {
isoInfo$minIF <- apply(
isoInfo[,na.omit(match(c('IF1','IF2'), colnames(isoInfo)) ),drop=FALSE],
1,
function(x) {
max(x, na.rm = TRUE)
}
)
isoInfo <- isoInfo[which(
isoInfo$minIF >= IFcutoff
),]
if(nrow(isoInfo) == 0) {
stop('No isoforms left after filtering via the "IFcutoff" argument.')
}
isoform_id <- isoInfo$isoform_id
}
if( switchAnalyzeRlist$sourceId == 'preDefinedSwitches' ) {
isoInfo <- isoInfo[which(
!is.na(isoInfo$dIF)
),]
isoform_id <- intersect(
isoform_id, isoInfo$isoform_id
)
}
### Remove if all is annotated as NA
if(!is.null(isoInfo$sub_cell_location)) {
if(all(is.na(isoInfo$sub_cell_location))) {
isoInfo$sub_cell_location <- NULL
}
}
if(!is.null(isoInfo$solubility_status)) {
if(all(is.na(isoInfo$solubility_status))) {
isoInfo$solubility_status <- NULL
}
}
### Extract ORF info
columnsToExtract <-
c('isoform_id', 'orfStartGenomic', 'orfEndGenomic','wasTrimmed', 'trimmedStartGenomic')
columnsToExtract <-
na.omit(match(
columnsToExtract,
colnames(switchAnalyzeRlist$orfAnalysis)
))
rowsToExtract <-
which(switchAnalyzeRlist$orfAnalysis$isoform_id %in% isoform_id)
orfInfo <-
switchAnalyzeRlist$orfAnalysis[rowsToExtract, columnsToExtract]
if(nrow(orfInfo) == 0) {
warning(
paste(
'There might somthing wrong with the switchAnalyzeRlist',
'- there are no ORF annoation matching the isoforms of interest:',
paste(isoform_id, collapse = ', '),
'. These isoforoms will be plotted as non-coding.',
sep=' '
)
)
### Add NAs manually
isoInfo$orfStartGenomic <- NA
isoInfo$orfEndGenomic <- NA
isoInfo$wasTrimmed <- FALSE
isoInfo$trimmedStartGenomic <- NA
} else {
inclTrimmedIsoforms <- FALSE
if( 'wasTrimmed' %in% colnames(orfInfo) ) {
if(any( orfInfo$wasTrimmed, na.rm = TRUE) ) {
inclTrimmedIsoforms <- TRUE
}
}
### Combine
isoInfo <- merge(isoInfo, orfInfo, by = 'isoform_id')
}
if (length(unique(isoInfo$gene_id)) > 1) {
stop(
'The isoforms supplied originates from more than one gene - a feature currently not supported. Please revise accordingly'
)
}
geneName <- paste(unique(isoInfo$gene_name), collapse = ',')
}
### Exon data
if(TRUE) {
exonInfo <-
switchAnalyzeRlist$exons[which(
switchAnalyzeRlist$exons$isoform_id %in% isoform_id
), ]
if (!length(exonInfo)) {
stop(
'It seems like there is no exon information advailable for the gene/transcripts supplied. Please update to the latest version of IsoformSwitchAnalyzeR and try again (re-import the data). If the problem persist contact the developer'
)
}
exonInfoSplit <- split(exonInfo, exonInfo$isoform_id)
chrName <- as.character(seqnames(exonInfo)[1])
}
### ORF data
if(TRUE) {
if (inclORF) {
orfStart <-
lapply(split(isoInfo$orfStartGenomic, isoInfo$isoform_id),
unique)
orfEnd <-
lapply(split(isoInfo$orfEndGenomic, isoInfo$isoform_id),
unique)
} else {
orfStart <- split(rep(NA, length(isoform_id)), isoform_id)
orfEnd <-
split(rep(NA, length(isoform_id)), isoform_id)
}
}
### Transcript type
if(TRUE) {
if (inclCodingPotential) {
isCoding <-
lapply(split(isoInfo$codingPotential, isoInfo$isoform_id),
unique)
}
if (inclPTC) {
isPTC <- lapply(split(isoInfo$PTC, isoInfo$isoform_id), unique)
}
}
### Extract basis annoation data
if(TRUE) {
### Make list with annotation
annotationList <- list()
### Domain data
if (inclDomainAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$domainAnalysis$isoform_id
)) {
DomainAnalysis <-
switchAnalyzeRlist$domainAnalysis[which(
switchAnalyzeRlist$domainAnalysis$isoform_id %in%
isoInfo$isoform_id
), ]
DomainAnalysis$isoform_id <-
factor(DomainAnalysis$isoform_id,
levels = unique(isoInfo$isoform_id))
DomainAnalysis$id <- 1:nrow(DomainAnalysis)
### Annotate structural variants
if( !is.null(DomainAnalysis$domain_isotype_simple)) {
DomainAnalysis$domain_sv <- ifelse(
DomainAnalysis$domain_isotype_simple == 'Reference',
yes = '',
no = ' (Non-ref Isotype)'
)
DomainAnalysis$hmm_name <- paste0(
DomainAnalysis$hmm_name,
DomainAnalysis$domain_sv
)
}
annotationList$protein_domain <- DomainAnalysis[,c('isoform_id','pfamStartGenomic','pfamEndGenomic','hmm_name','id')]
}
}
if (inclIdrAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$idrAnalysis$isoform_id
)) {
idrAnalysis <-
switchAnalyzeRlist$idrAnalysis[which(
switchAnalyzeRlist$idrAnalysis$isoform_id %in%
isoInfo$isoform_id
), ]
idrAnalysis$isoform_id <-
factor(idrAnalysis$isoform_id,
levels = unique(isoInfo$isoform_id))
#idrAnalysis$idrName <- 'IDR'
idrAnalysis$id <- 1:nrow(idrAnalysis)
annotationList$idr <- idrAnalysis[,c('isoform_id','idrStartGenomic','idrEndGenomic','id')]
}
}
if (inclSignalPAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$signalPeptideAnalysis$isoform_id
)) {
signalPanalysis <-
switchAnalyzeRlist$signalPeptideAnalysis[which(
switchAnalyzeRlist$signalPeptideAnalysis$isoform_id %in%
isoInfo$isoform_id
), ]
signalPanalysis$genomicClevageAfter <-
unlist(signalPanalysis$genomicClevageAfter)
### Signal P region
signalPdata <- isoInfo[,c('isoform_id','orfStartGenomic')]
colnames(signalPdata)[2] <- 'spStartGenomic'
signalPdata$spEndGenomic <- signalPanalysis$genomicClevageAfter[match(
signalPdata$isoform_id, signalPanalysis$isoform_id
)]
signalPdata$id <- signalPdata$isoform_id
signalPanalysis$isoform_id <-
factor(signalPanalysis$isoform_id,
levels = unique(isoInfo$isoform_id))
annotationList$signal_peptide <- signalPdata
}
}
if (plotTopology) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$topologyAnalysis$isoform_id
)) {
tolologyAnalysis <-
switchAnalyzeRlist$topologyAnalysis[which(
switchAnalyzeRlist$topologyAnalysis$isoform_id %in%
isoInfo$isoform_id
), ]
tolologyAnalysis$isoform_id <-
factor(tolologyAnalysis$isoform_id,
levels = unique(isoInfo$isoform_id))
tolologyAnalysis$id <- 1:nrow(tolologyAnalysis)
annotationList$topology <- tolologyAnalysis[,c('isoform_id','regionStartGenomic','regionEndGenomic','region_type','id')]
}
}
}
### Domain sites
if(TRUE) {
if (inclDomainAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$domainAnalysis$isoform_id
)) {
domainStart <-
split(
DomainAnalysis$pfamStartGenomic,
DomainAnalysis$isoform_id,
drop = FALSE
)
domainEnd <-
split(DomainAnalysis$pfamEndGenomic,
DomainAnalysis$isoform_id,
drop = FALSE)
domainName <-
split(DomainAnalysis$hmm_name,
DomainAnalysis$isoform_id,
drop = FALSE)
### Handle if there are any none-unique domain names:
if (ifMultipleIdenticalAnnotation == 'number') {
domainName <- lapply(domainName, function(aVec) {
duplicatedIndex <- which(duplicated(aVec))
if (length(duplicatedIndex)) {
aVec[duplicatedIndex] <-
paste(aVec[duplicatedIndex],
1:length(duplicatedIndex),
sep = '.')
}
return(aVec)
})
} else if (ifMultipleIdenticalAnnotation == 'summarize') {
domainName <- lapply(domainName, function(aVec) {
nameTable <- as.data.frame(
table(aVec),
stringsAsFactors = FALSE
)
# only modify those with mutiple instances
nameTable$newName <- nameTable$aVec
modifyIndex <- which(nameTable$Freq > 1)
nameTable$newName[modifyIndex] <-
paste(nameTable$aVec[modifyIndex],
' (x',
nameTable$Freq[modifyIndex],
')',
sep = '')
newVec <-
nameTable$newName[match(aVec, nameTable$aVec)]
})
} else if (ifMultipleIdenticalAnnotation != 'ignore') {
stop(
'An error occured with ifMultipleIdenticalAnnotation - please contact developers with reproducible example'
)
}
} else {
domainStart <- NULL # By setting them to null they are ignore from hereon out
domainEnd <- NULL
}
} else {
domainStart <- NULL # By setting them to null they are ignore from hereon out
domainEnd <- NULL
}
}
### IDR Sites
if(TRUE) {
if (inclIdrAnalysis) {
if(
any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$idrAnalysis$isoform_id
)
) {
idrStart <-
split(
idrAnalysis$idrStartGenomic,
idrAnalysis$isoform_id,
drop = FALSE
)
idrEnd <-
split(idrAnalysis$idrEndGenomic,
idrAnalysis$isoform_id,
drop = FALSE)
idrName <-
split(idrAnalysis$idr_type,
idrAnalysis$isoform_id,
drop = FALSE)
### Handle if there are any none-unique domain names
if(TRUE) {
if (ifMultipleIdenticalAnnotation == 'number') {
idrName <- lapply(idrName, function(aVec) {
duplicatedIndex <- which(duplicated(aVec))
if (length(duplicatedIndex)) {
aVec[duplicatedIndex] <-
paste(aVec[duplicatedIndex],
1:length(duplicatedIndex),
sep = '.')
}
return(aVec)
})
} else if (ifMultipleIdenticalAnnotation == 'summarize') {
idrName <- lapply(idrName, function(aVec) {
nameTable <- as.data.frame(
table(aVec),
stringsAsFactors = FALSE
)
# only modify those with mutiple instances
nameTable$newName <- nameTable$aVec
modifyIndex <- which(nameTable$Freq > 1)
nameTable$newName[modifyIndex] <-
paste(nameTable$aVec[modifyIndex],
' (x',
nameTable$Freq[modifyIndex],
')',
sep = '')
newVec <-
nameTable$newName[match(aVec, nameTable$aVec)]
})
} else if (ifMultipleIdenticalAnnotation != 'ignore') {
stop(
'An error occured with ifMultipleIdenticalAnnotation - please contact developers with reproducible example'
)
}
}
} else {
idrStart <- NULL # By setting them to null they are ignore from hereon out
idrEnd <- NULL
}
} else {
idrStart <- NULL # By setting them to null they are ignore from hereon out
idrEnd <- NULL
}
}
### Signal peptide data
if(TRUE) {
if (inclSignalPAnalysis) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$signalPeptideAnalysis$isoform_id
)) {
cleaveageAfter <-
split(
signalPanalysis$genomicClevageAfter,
signalPanalysis$isoform_id,
drop = FALSE
)
} else {
cleaveageAfter <-
NULL # By setting them to null they are ignore from hereon out
}
} else {
cleaveageAfter <-
NULL # By setting them to null they are ignore from hereon out
}
}
### Toplogy
if(TRUE) {
if (plotTopology) {
if (any(
isoInfo$isoform_id %in%
switchAnalyzeRlist$topologyAnalysis$isoform_id
)) {
toplologyStart <-
split(
tolologyAnalysis$regionStartGenomic,
tolologyAnalysis$isoform_id,
drop = FALSE
)
toplologyEnd <-
split(tolologyAnalysis$regionEndGenomic,
tolologyAnalysis$isoform_id,
drop = FALSE)
toplologyType <-
split(tolologyAnalysis$region_type,
tolologyAnalysis$isoform_id,
drop = FALSE)
} else {
toplologyStart <- NULL # By setting them to null they are ignore from hereon out
toplologyEnd <- NULL
# turn of visualization since no data
plotTopology <- FALSE
}
} else {
toplologyStart <- NULL # By setting them to null they are ignore from hereon out
toplologyEnd <- NULL
# turn of visualization since no data
plotTopology <- FALSE
}
}
### Trimmed sites
if(TRUE) {
if( inclTrimmedIsoforms ) {
trimmedInfo <- orfInfo[,c('isoform_id','trimmedStartGenomic','orfEndGenomic')]
trimmedInfo$orfEndGenomic[which(is.na(trimmedInfo$trimmedStartGenomic))] <- NA
trimmedInfo$name <- NA
trimmedStart <-
split(
trimmedInfo$trimmedStartGenomic,
trimmedInfo$isoform_id,
drop = FALSE
)
trimmedEnd <-
split(trimmedInfo$orfEndGenomic,
trimmedInfo$isoform_id,
drop = FALSE)
} else {
trimmedStart <- NULL # By setting them to null they are ignore from hereon out
trimmedEnd <- NULL
}
}
}
### Align and massage regions
if(TRUE) {
### Align everything and annoate each region
if(TRUE) {
### Loop over each transcript and make the data.frame with all the annotation data (this is currently the rate limiting step)
myTranscriptPlotDataList <- list()
for (i in seq(along.with = exonInfoSplit)) {
# extract data
transcriptName <- names(exonInfoSplit)[i]
localExons <- exonInfoSplit[[transcriptName]]
# extract local values of where to cut the transcript
localOrfStart <-
orfStart [[transcriptName]]
localOrfEnd <-
orfEnd [[transcriptName]] + 1
localDomainStart <-
domainStart [[transcriptName]]
localDomainEnd <-
domainEnd [[transcriptName]] + 1
localIdrStart <-
idrStart [[transcriptName]]
localIdrEnd <-
idrEnd [[transcriptName]] + 1
localTopStart <-
toplologyStart[[transcriptName]]
localTopEnd <-
toplologyEnd [[transcriptName]] + 1
localtrimmedStart <-
trimmedStart [[transcriptName]]
localtrimmedEnd <-
trimmedEnd [[transcriptName]] + 1
localPepticeCleaveage <-
cleaveageAfter[[transcriptName]]
myCutValues <-
unique(
c(
localOrfStart,
localOrfEnd,
localDomainStart,
localDomainEnd,
localIdrStart,
localIdrEnd,
localTopStart,
localTopEnd,
localtrimmedStart,
localtrimmedEnd,
localPepticeCleaveage
)
) # NULLs are just removed
# cut the exons into smaller part based on the ORF and domain coordinats (if needed)
if (length(myCutValues) & !is.na(myCutValues[1])) {
localExonsDevided <-
cutGRanges(aGRange = localExons, cutValues = myCutValues)
} else {
localExonsDevided <- localExons[, 0]
}
### Add annotation
## add standard annotation
localExonsDevided$type <- 'utr'
localExonsDevided$Domain <- ' transcript'
localExonsDevided$topology <- 'none'
## modify if needed
# ORF
if(length(localOrfStart)) {
if (!is.na(localOrfStart)) {
coordinatPair <- c(localOrfStart, localOrfEnd)
orfRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$type[queryHits(findOverlaps(
subject = orfRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- 'cds'
}
}
# domain - loop over each domain
if (length(localDomainStart)) {
for (j in 1:length(localDomainStart)) {
coordinatPair <- c(localDomainStart[j], localDomainEnd[j])
if( all( !is.na(coordinatPair)) ) {
domainRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$Domain[queryHits(findOverlaps(
subject = domainRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- domainName[[transcriptName]][j]
}
}
}
# IDR
if (length(localIdrStart)) {
for (j in 1:length(localIdrStart)) {
coordinatPair <- c(localIdrStart[j], localIdrEnd[j])
if( all( !is.na(coordinatPair)) ) {
domainRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$Domain[queryHits(findOverlaps(
subject = domainRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- idrName[[transcriptName]][j]
}
}
}
# signal peptide
if (length(localPepticeCleaveage)) {
coordinatPair <- c(localOrfStart, localPepticeCleaveage)
if( all( !is.na(coordinatPair)) ) {
peptideRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$Domain[queryHits(findOverlaps(
subject = peptideRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- 'Signal Peptide'
}
}
# trimmed
if (length(localtrimmedStart)) {
for (j in 1:length(localtrimmedStart)) {
coordinatPair <- c(localtrimmedStart[j], localtrimmedEnd[j])
if( all( !is.na(coordinatPair)) ) {
domainRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$Domain[queryHits(findOverlaps(
subject = domainRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- 'Not Analyzed'
}
}
}
# topology - loop over each domain
if (length(localTopStart)) {
for (j in 1:length(localTopStart)) {
coordinatPair <- c(localTopStart[j], localTopEnd[j])
if( all( !is.na(coordinatPair)) ) {
domainRange <-
IRanges(min(coordinatPair), max(coordinatPair))
localExonsDevided$topology[queryHits(findOverlaps(
subject = domainRange,
query = ranges(localExonsDevided),
type = 'within'
))] <- toplologyType[[transcriptName]][j]
}
}
}
# convert to df
localExonsDf <- as.data.frame(localExonsDevided)
### Massage
localExonsDf$transcript <- transcriptName
### determine transcript type
if (inclCodingPotential) {
localCoding <- isCoding[[transcriptName]]
} else {
### I no prediction default to annotation
if( ! is.na(localOrfStart) ) {
localCoding <- TRUE
} else {
localCoding <- NULL
}
}
if (inclPTC) {
localPTC <- isPTC[[transcriptName]]
} else {
localPTC <- NULL
}
localExonsDf$seqnames <-
determineTranscriptClass(ptc = localPTC , coding = localCoding)
colnames(localExonsDf)[1] <- 'seqnames'
# save
myTranscriptPlotDataList[[transcriptName]] <- localExonsDf
}
myTranscriptPlotData <- do.call(rbind, myTranscriptPlotDataList)
}
# myTranscriptPlotData
### Correct names !!! where Tx Names are changed !!!!
if (TRUE) {
### correct transcript names
# Create name annotation (this can be omitted when ggplots astetics mapping against type works)
nameDF <- data.frame(
oldTxName = unique(myTranscriptPlotData$transcript),
newTxName = unique(myTranscriptPlotData$transcript),
stringsAsFactors = FALSE
)
### Modify if class code is defined
if ('class_code' %in% colnames(isoInfo)) {
nameDF$newTxName <- paste(
nameDF$newTxName,
' (',
isoInfo$class_code[match(nameDF$oldTxName, isoInfo$isoform_id)],
')',
sep = ''
)
}
if ( isConditional ) {
### Interpret direction
isoInfo$direction <- 'Unchanged usage'
isoInfo$direction[which(isoInfo$dIF > dIFcutoff )] <- 'Increased usage'
isoInfo$direction[which(isoInfo$dIF < dIFcutoff * -1)] <- 'Decreased usage'
if( ! optimizeForCombinedPlot ) {
### Add dIF
if( ! all(isoInfo$dIF %in% c(0, Inf, -Inf)) ) {
isoInfo$direction <- paste(
isoInfo$direction,
': dIF =',
formatC(round(isoInfo$dIF, digits = 2),digits = 2, format='f') ,
sep=' '
)
}
### Add q-values
if(any( !is.na(isoInfo$isoform_switch_q_value))) {
if( ! all(isoInfo$isoform_switch_q_value %in% c(1, -Inf)) ) {
isoInfo$sig <- evalSig(isoInfo$isoform_switch_q_value, alphas = alphas)
isoInfo$direction <- startCapitalLetter(
paste0(
isoInfo$direction,
' (',
isoInfo$sig,
')'
)
)
}
}
}
### Make new name
nameDF$newTxName <- paste(
nameDF$newTxName,
'\n(',
isoInfo$direction[match(nameDF$oldTxName, isoInfo$isoform_id)],
')',
sep = ''
)
}
### Modify if sub-cell location is defined
if( 'sub_cell_location' %in% colnames(isoInfo) ) {
matchVec <- match(nameDF$oldTxName, isoInfo$isoform_id)
if(abbreviateLocations) {
isoInfo$sub_cell_location <- sapply(
str_split(isoInfo$sub_cell_location, ','),
function(x) {
x <- gsub(pattern = 'Cell_membrane' , replacement = 'Memb' , x = x)
x <- gsub(pattern = 'Cytoplasm' , replacement = 'Cyto' , x = x)
x <- gsub(pattern = 'Endoplasmic_reticulum', replacement = 'ER' , x = x)
x <- gsub(pattern = 'Extracellular' , replacement = 'ExtCell', x = x)
x <- gsub(pattern = 'Golgi_apparatus' , replacement = 'Golgi' , x = x)
x <- gsub(pattern = 'Lysosome_Vacuole' , replacement = 'Lys' , x = x)
x <- gsub(pattern = 'Mitochondrion' , replacement = 'Mito' , x = x)
x <- gsub(pattern = 'Nucleus' , replacement = 'Nucl' , x = x)
x <- gsub(pattern = 'Peroxisome' , replacement = 'Perox' , x = x)
x <- gsub(pattern = 'Plastid' , replacement = 'Plastid', x = x)
x <- paste(x, collapse = ', ')
return(x)
}
)
}
nameDF$newTxName <- paste0(
nameDF$newTxName,
'\n(Location: ',
isoInfo$sub_cell_location[match(
nameDF$oldTxName,
isoInfo$isoform_id
)],
')'
)
}
### Modify if solubility location is defined
if( 'solubility_status' %in% colnames(isoInfo) ) {
matchVec <- match(nameDF$oldTxName, isoInfo$isoform_id)
nameDF$newTxName <- paste0(
nameDF$newTxName,
'\n(',
gsub('_',' ', isoInfo$solubility_status[match(
nameDF$oldTxName,
isoInfo$isoform_id
)]),
')'
)
}
myTranscriptPlotData$transcript <-
nameDF$newTxName[match(
myTranscriptPlotData$transcript, nameDF$oldTxName
)]
### Factorize order
supposedOrder <-
c('Coding',
'Non-coding',
'NMD Insensitive',
'NMD Sensitive',
'Transcripts')
supposedOrder <-
supposedOrder[which(
supposedOrder %in% myTranscriptPlotData$seqnames
)]
myTranscriptPlotData$seqnames <-
factor(myTranscriptPlotData$seqnames)
newOrder <-
match(levels(myTranscriptPlotData$seqnames),
supposedOrder)
myTranscriptPlotData$seqnames <-
factor(myTranscriptPlotData$seqnames,
levels = levels(myTranscriptPlotData$seqnames)[newOrder])
}
### Rescale coordinats if nessesary
if (rescaleTranscripts) {
# Might as well work with smaller numbers
myTranscriptPlotData[, c('start', 'end')] <-
myTranscriptPlotData[, c('start', 'end')] -
min(myTranscriptPlotData[, c('start', 'end')]) + 1
### create conversion table from origial coordiants to rescaled values
allCoordinats <-
sort(unique(
c(
myTranscriptPlotData$start,
myTranscriptPlotData$end
)
))
myCoordinats <-
data.frame(orgCoordinates = allCoordinats,
newCoordinates = allCoordinats)
for (i in 2:nrow(myCoordinats)) {
orgDistance <-
myCoordinats$orgCoordinates[i] -
myCoordinats$orgCoordinates[i - 1]
newDistance <- max(c(1, round(
orgDistance^(1/rescaleRoot)
)))
difference <- orgDistance - newDistance
myCoordinats$newCoordinates [i:nrow(myCoordinats)] <-
myCoordinats$newCoordinates [i:nrow(myCoordinats)] - difference
}
# replace original values
myTranscriptPlotData$start <-
myCoordinats$newCoordinates[match(
myTranscriptPlotData$start,
table = myCoordinats$orgCoordinates
)]
myTranscriptPlotData$end <-
myCoordinats$newCoordinates[match(
myTranscriptPlotData$end,
table = myCoordinats$orgCoordinates
)]
}
### Revers coordinats if nesseary (and transcript is on minus strand)
invertCoordinats <-
reverseMinus & as.character(exonInfo@strand)[1] == '-' # exonInfo
if (invertCoordinats) {
# extract min coordinat
minCoordinat <- min(myTranscriptPlotData[, c('start', 'end')])
# transpose to
myTranscriptPlotData[, c('start', 'end')] <-
myTranscriptPlotData[, c('start', 'end')] - minCoordinat + 1
# calculate how much to extract
subtractNr <- max(myTranscriptPlotData[, c('start', 'end')])
# calculate new coordinats (by subtracting everthing becomes negative, and abs inverts to postive = evertyhing is inversed)
newCoordinats <-
abs(myTranscriptPlotData[, c('start', 'end')] - subtractNr)
# overwrite old coordinats
myTranscriptPlotData$start <- newCoordinats$start
myTranscriptPlotData$end <- newCoordinats$end
myTranscriptPlotData$strand <- '+'
# transpose back so min coordiant is the same
myTranscriptPlotData[, c('start', 'end')] <-
myTranscriptPlotData[, c('start', 'end')] + minCoordinat
}
### order data
if(TRUE) {
### Order by transcript category and name and add index (index ensures names and transcipts are properly plotted)
myTranscriptPlotData <-
myTranscriptPlotData[order(myTranscriptPlotData$seqnames,
myTranscriptPlotData$transcript,
decreasing = TRUE), ]
myTranscriptPlotData$idNr <-
match(myTranscriptPlotData$transcript ,
unique(myTranscriptPlotData$transcript))
}
}
### Create objects for plot parts
if(TRUE) {
### Create lines for toplogy
if(plotTopology) {
toplogyInfo <-
myTranscriptPlotData %>%
filter(topology %in% c(
'signal',
'outside',
'TMhelix',
'inside'
)) %>%
mutate(
topGroup = 1:dplyr::n(),
Topology = dplyr::case_when(
topology == 'signal' ~ 'Signal Peptide',
topology == 'outside' ~ 'Extracellular',
topology == 'inside' ~ 'Intracellular',
topology == 'TMhelix' ~ 'TM helix',
TRUE ~ 'Something with toplogy assignment went wrong - contact developer'
),
idNr = idNr + rectHegith * codingWidthFactor + rectHegith / 3 #lift them up
) %>%
select(idNr, seqnames, start, end, Topology, topGroup) %>%
tidyr::pivot_longer(cols = c('start','end')) %>%
as.data.frame()
}
### Create coordiants to rectangels
if (TRUE) {
# ### Convert coordiants to rectangels coordinats (for plotting) and order them according to draw order
### calculate rectangle coordinates
myTranscriptPlotData$ymin <- myTranscriptPlotData$start
myTranscriptPlotData$ymax <- myTranscriptPlotData$end
myTranscriptPlotData$xmin <-
myTranscriptPlotData$idNr - rectHegith
myTranscriptPlotData$xmax <-
myTranscriptPlotData$idNr + rectHegith
### Change with of coding regions
codingIndex <- which(myTranscriptPlotData$type == 'cds')
myTranscriptPlotData$xmin[codingIndex] <-
myTranscriptPlotData$idNr[codingIndex] -
(rectHegith * codingWidthFactor)
myTranscriptPlotData$xmax[codingIndex] <-
myTranscriptPlotData$idNr[codingIndex] +
(rectHegith * codingWidthFactor)
### Change order to reflect annotationImportance
if(TRUE) {
### Create vector with supposed ordering
annotNameList <- list(
transcript = ' transcript',
notAnalyzed = "Not Analyzed"
)
if(!is.null(domainStart)) {
annotNameList$protein_domain <- unique(unlist(domainName))
}
if(!is.null(idrStart)) {
annotNameList$idr <- unique(unlist(idrName))
}
if(!is.null(cleaveageAfter)) {
annotNameList$signal_peptide <- 'Signal Peptide'
}
annotNameListOrdered <- unlist( annotNameList[c(
'transcript',
'notAnalyzed',
rev(annotationImportance)
)] )
### Reorder data
myTranscriptPlotData$DomainRanking <- match(myTranscriptPlotData$Domain, annotNameListOrdered)
myTranscriptPlotData <- myTranscriptPlotData[order(
myTranscriptPlotData$DomainRanking,
myTranscriptPlotData$seqnames,
myTranscriptPlotData$transcript,
decreasing = FALSE
),]
}
}
### Create transcript inton lines with arrows
if (TRUE) {
totalLengths <-
diff(range(
c(
myTranscriptPlotData$ymin,
myTranscriptPlotData$ymax
)
))
byFactor <- totalLengths / nrArrows
myTranscriptPlotDataSplit <-
split(myTranscriptPlotData, f = myTranscriptPlotData$idNr)
arrowlineDataCombined <-
do.call(rbind, lapply(myTranscriptPlotDataSplit, function(aDF) {
# aDF <- myTranscriptPlotDataSplit[[1]]
# extract introns (if coordinats are inverted start have the largest coordinat now)
if (invertCoordinats) {
localIntrons <-
data.frame(gaps(IRanges(
start = aDF$end, end = aDF$start
)))
} else {
localIntrons <-
data.frame(gaps(IRanges(
start = aDF$start, end = aDF$end
)))
}
if (nrow(localIntrons)) {
# Determine munber of arrows based on total intronseize compare to all transcript
totalIntronSize <- sum(localIntrons$width)
localNrArrows <-
totalIntronSize / totalLengths * nrArrows
localIntrons$nrArrows <-
floor(localIntrons$width /
sum(localIntrons$width) * localNrArrows)
localIntrons$index <-
seq(along.with = localIntrons$start)
# for each intron make the calculate number of arrows (min 1 arrow pr intron since the seq(+2) will always give two coordiants)
localArrowlineData <-
do.call(rbind, lapply(split(
localIntrons,
f = seq(along.with = localIntrons$start)
), function(localDF) {
# localDF <- localIntrons[1,]
mySeq <-
seq(
min(localDF$start),
max(localDF$end) + 1,
length.out = localDF$nrArrows + 2
)
localArrowlineData <-
data.frame(
seqnames = aDF$seqnames[1],
x = aDF$idNr[1],
y = mySeq[-length(mySeq)] - 1,
yend = mySeq[-1],
nrArrows = localDF$nrArrows
)
return(localArrowlineData)
}))
# reverse arrow direction if transcript is on minus strand (and reverse is off) - nessesary since calculations are done on + strand since IRanges cannot handle negative widths
if (!reverseMinus &
as.character(exonInfo@strand)[1] == '-') {
localArrowlineData <-
data.frame(
seqnames = localArrowlineData$seqnames,
x = localArrowlineData$x,
y = localArrowlineData$yend,
yend = localArrowlineData$y,
nrArrows = localArrowlineData$nrArrows
)
}
return(localArrowlineData)
} else {
localArrowlineData <-
data.frame(
seqnames = aDF$seqnames[1],
x = aDF$idNr[1],
y = NA,
yend = NA,
nrArrows = c(0, 1)
)
return(localArrowlineData)
}
}))
arrowlineDataArrows <-
arrowlineDataCombined[which(arrowlineDataCombined$nrArrows != 0), ]
arrowlineDataLines <-
arrowlineDataCombined[which(arrowlineDataCombined$nrArrows == 0), ]
}
### create data.frame for converting between index id and transcript name
idData <-
unique(myTranscriptPlotData[, c('seqnames', 'transcript', 'idNr')])
### create color code for domains
if(TRUE) {
domainsFound <-
unique(myTranscriptPlotData$Domain [which(
! myTranscriptPlotData$Domain %in% c(' transcript', "Not Analyzed")
)])
### Reorder
domainsFound <- sort(domainsFound)
domainsFound <- domainsFound[c(
which( domainsFound == "Signal Peptide"),
which( domainsFound != "Signal Peptide")
)]
### Get colors
if(TRUE) {
if (length(domainsFound) == 0) {
domainsColor <- NULL
} else if (length(domainsFound) < 3) {
#domainsColor <-
# RColorBrewer::brewer.pal(
# n = 3,
# name = 'Dark2'
# )[2:(length(domainsFound) + 1)]
domainsColor <-
RColorBrewer::brewer.pal(
n = 12,
name = 'Paired'
)[c(2,4,6)[1:length(domainsFound)]]
} else if (length(domainsFound) > 12) {
gg_color_hue <- function(n) {
hues <- seq(15, 375, length = n + 1)
hcl(h = hues,
l = 65,
c = 100)[1:n]
}
domainsColor <- gg_color_hue(length(domainsFound))
} else {
domainsColor <-
RColorBrewer::brewer.pal(n = length(domainsFound), name = 'Paired')
}
}
### Fix order
if( "Not Analyzed" %in% myTranscriptPlotData$Domain ) {
domainsFound <- c(domainsFound, "Not Analyzed")
correspondingColors <- c(
"#161616", # for ' transcript'
domainsColor,
'#595959' # For "not analyzed"
)
### Move "not analyzed" color to its corresponding position
apperanceInData <- sort(unique(myTranscriptPlotData$Domain))
moveToIndex <- which(sort(apperanceInData) == "Not Analyzed")
correspondingColors <- c(
correspondingColors[1:(moveToIndex-1)],
correspondingColors[length(correspondingColors)],
correspondingColors[(moveToIndex):(length(correspondingColors)-1)]
)
} else {
correspondingColors <- c(
"#161616", # for ' transcript'
domainsColor
)
}
}
### Combined plotting
if (optimizeForCombinedPlot) {
### Collect all labels
allLabels <- c(
condition1,
condition2,
unique(domainsFound)
)
if(plotTopology) {
allLabels <- c(
allLabels,
unique(toplogyInfo$Topology)
)
}
### Find length of longest label
analyzeStrandCompositionInWhiteSpaces <-
function(aString) {
# aString <- 'Ab1'
round(sum(sapply(
strsplit(aString, '')[[1]],
function(aCharacter) {
# Test if whitespace
if (aCharacter == ' ') {
return(1)
}
# Test if number
if (!is.na(suppressWarnings(as.integer(aCharacter)))) {
return(2) # whitespace pr number
}
# test symbols
if (aCharacter == '_') {
return(2) # whitespace pr character
}
# test symbols
if (aCharacter == '.') {
return(1) # whitespace pr numbers
}
# test upper
if (aCharacter == toupper(aCharacter)) {
return(2.4) # whitespace pr uppercase
}
# else it is probably lower
return(1.8) # whitespace pr lowercase
})))
}
maxCharacter <-
max(c(
sapply(allLabels, analyzeStrandCompositionInWhiteSpaces) ,
50
))
### Modify names to match length
modifyNames <- function(aVec, extendToLength) {
tmp <- sapply(aVec, function(x) {
currentLength <- analyzeStrandCompositionInWhiteSpaces(x)
whitespacesToAdd <-
round(extendToLength - currentLength - 1)
if (whitespacesToAdd > 0) {
x <-
paste(x, paste(rep(
' ', whitespacesToAdd
), collapse = ''), collapse = '')
}
return(x)
})
names(tmp) <- NULL
return(tmp)
}
### Modify them
domainsFound <- modifyNames(domainsFound, maxCharacter)
modifiedNames <-
data.frame(
org = allLabels,
new = modifyNames(allLabels, maxCharacter),
stringsAsFactors = FALSE
)
indexToModify <-
which(myTranscriptPlotData$Domain != ' transcript')
myTranscriptPlotData$Domain[indexToModify] <-
modifiedNames$new[match(
myTranscriptPlotData$Domain[indexToModify] , modifiedNames$org
)]
if(plotTopology) {
toplogyInfo$Topology <-
modifiedNames$new[match(
toplogyInfo$Topology, modifiedNames$org
)]
}
}
### factorize seqnames for all 3 datasets to ensure correct facetting
if(TRUE) {
myTranscriptPlotData$seqnames <-
factor(myTranscriptPlotData$seqnames, levels = supposedOrder)
arrowlineDataArrows$seqnames <-
factor(arrowlineDataArrows$seqnames, levels = supposedOrder)
arrowlineDataLines$seqnames <-
factor(arrowlineDataLines$seqnames, levels = supposedOrder)
idData$seqnames <-
factor(idData$seqnames, levels = supposedOrder)
if(plotTopology) {
toplogyInfo$seqnames <-
factor(toplogyInfo$seqnames, levels = supposedOrder)
}
}
}
### Build plot
if(TRUE) {
myPlot <- ggplot()
### Introns
if (nrow(arrowlineDataLines)) {
myPlot <-
myPlot + geom_segment(data = arrowlineDataLines, aes(
x = y,
xend = yend,
y = x,
yend = x
))
}
if (nrow(arrowlineDataArrows)) {
myPlot <-
myPlot + geom_segment(
data = arrowlineDataArrows,
aes(
x = y,
xend = yend,
y = x,
yend = x
),
arrow = arrow(length = unit(arrowSize, "cm"))
) # intron arrows
}
### transcripts
if(TRUE) {
myPlot <- myPlot +
geom_rect(
data = myTranscriptPlotData,
aes(
xmin = ymin,
ymin = xmin,
xmax = ymax,
ymax = xmax,
fill = Domain
)
)
### Transcript color and theme
myPlot <- myPlot +
scale_fill_manual(
breaks = c('transcript',domainsFound),
values = correspondingColors,
na.value = '#161616'
) + # Correct domian color code so transcripts are black and not shown
scale_y_continuous(breaks = idData$idNr, labels = idData$transcript) # change index numbers back to names
}
### topology
if(plotTopology) {
nToplogy <- length(unique(toplogyInfo$Topology))
#lineColors <- grDevices::gray.colors(n = nToplogy, start = 0.3, end = 0.8)
lineColors <- c(
'#7DC462',
'#774FA0',
'#0D95D0',
'#E72F52'
)[1:nToplogy]
#lineColors <- RColorBrewer::brewer.pal(
# n = 8,
# name = 'Dark2'
#)[c(8, 4, 1)[1:nToplogy]]
myPlot <-
myPlot +
geom_line(
aes(
x = value,
y = idNr,
group = topGroup,
color = Topology
),
data = toplogyInfo,
linewidth = 3
) +
scale_color_manual(values = lineColors)
}
### Optimize apperance
if(TRUE) {
### style and themes
myPlot <-
myPlot +
localTheme + theme(strip.text.y = element_text(angle = 0)) + # change theme and rotate facette labes (ensures readability even though frew are pressent)
theme(axis.title.y = element_blank()) + # remove y-axis label
theme(strip.background = element_rect(fill = "white", linewidth = 0.5))
# facette against transcript type if nessesary
if (!all(supposedOrder == 'Transcripts')) {
myPlot <-
myPlot + facet_grid(seqnames ~ ., scales = 'free_y', space = 'free')
}
# Modify X axis
if (!plotXaxis) {
# remove axis if rescaled
myPlot <-
myPlot + theme(
axis.line = element_blank(),
axis.text.x = element_blank(),
axis.ticks = element_blank(),
axis.title.x = element_blank()
)
} else {
# add chr name
myPlot <- myPlot + labs(x = chrName)
}
if( ! optimizeForCombinedPlot ) {
if( isConditional ) {
if( any(grepl('^placeholder_1$|^placeholder_2$', c(condition1, condition2)) ) ) {
myPlot <- myPlot + labs(title = paste(
'The isoform switch in',
geneName,
sep = ' '
))
} else {
myPlot <- myPlot + labs(title = paste(
'The isoform switch in',
geneName,
paste0(' (', condition1, ' vs ', condition2,')'),
sep = ' '
))
}
} else {
myPlot <- myPlot + labs(title = paste(
'The isoforms in',
geneName,
sep = ' '
))
}
}
}
}
return(myPlot)
}
expressionAnalysisPlot <- function(
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
condition1 = NULL,
condition2 = NULL,
IFcutoff = 0.05,
addErrorbars = TRUE,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
alphas = c(0.05, 0.001),
extendFactor = 0.05,
logYaxis = FALSE,
optimizeForCombinedPlot = FALSE,
localTheme = theme_bw()
) {
### Check input
if (TRUE) {
# check switchAnalyzeRlist
if (class(switchAnalyzeRlist) != 'switchAnalyzeRlist') {
stop(
'The object supplied to \'switchAnalyzeRlist\' is not a \'switchAnalyzeRlist\''
)
}
if( switchAnalyzeRlist$sourceId == 'preDefinedSwitches' ) {
stop(
paste(
'The switchAnalyzeRlist is made from pre-defined isoform switches',
'which means it is made without defining conditions (as it should be).',
'\nThis also means it cannot used to plot conditional expression -',
'if that is your intention you need to create a new',
'switchAnalyzeRlist with the importRdata() function and start over.',
sep = ' '
)
)
}
# check isoform and gene name input
idInfoCheck <- sum(c(is.null(gene), is.null(isoform_id)))
if (idInfoCheck != 1) {
if (idInfoCheck == 0) {
stop('One of \'gene\' or \'isoform_id\' must be given as input')
}
if (idInfoCheck == 2) {
stop('Only one of \'gene\' or \'isoform_id\' can be supplied')
}
}
if (!is.logical(addErrorbars)) {
stop('The argument given to addErrorbars must be a logical')
}
if (!is.logical(confidenceIntervalErrorbars)) {
stop('The argument given to addErrorbars must be a logical')
}
if (confidenceInterval < 0 | confidenceInterval > 1) {
stop(
'The argument given to confidenceInterval must be a number in the interval [0,1]'
)
}
if (extendFactor < 0 | extendFactor > 1) {
stop('The argument given to extendFactor must be a number in the interval [0,1]')
}
# Sig levels
if (length(alphas) != 2) {
stop('A vector of length 2 must be given to the argument \'alphas\'')
}
if (any(alphas < 0) |
any(alphas > 1)) {
stop('The \'alphas\' parameter must be numeric between 0 and 1 ([0,1]).')
}
if (any(alphas > 0.05)) {
warning(
'Most journals and scientists consider an alpha larger than 0.05 untrustworthy. We therefore recommend using alpha values smaller than or queal to 0.05'
)
}
# chech conditions
if (TRUE) {
### Identify conditions
allConditionPairs <-
unique(switchAnalyzeRlist$isoformFeatures[,c(
'condition_1', 'condition_2'
)])
if (nrow(allConditionPairs) > 1) {
if (missing(condition1) | missing(condition2)) {
stop(
'Both the \'condition1\' and \'condition2\' arguments must be supplied (when there is more than two comparisons)'
)
}
if (is.null(condition1) | is.null(condition2)) {
stop(
'Both the \'condition1\' and \'condition2\' arguments must be supplied (when there is more than two comparisons)'
)
}
if (is.null(switchAnalyzeRlist$conditions)) {
stop(
'Please make sure the switchAnalyzeRlist is properly constructed - it is missing the \'condition\' argument'
)
}
if (!all(
c(condition1, condition2) %in%
switchAnalyzeRlist$conditions$condition
)) {
stop(
paste(
'Both condition arguments must be eith of: \'',
paste(
switchAnalyzeRlist$conditions$condition,
collapse = '\', \''
),
'\'',
sep = ''
)
)
}
if (condition1 == condition2) {
stop(
'The \'condition1\' and \'condition2\' arguments must be different'
)
}
levelsToMatch <- c(condition1, condition2)
conditionsFound <-
apply(allConditionPairs, 1, function(x) {
x[1] == condition1 & x[2] == condition2
})
if (!any(conditionsFound)) {
# the the conditions are not found try revers order
conditionsFound <-
apply(allConditionPairs, 1, function(x) {
x[2] == condition1 & x[1] == condition2
})
# if now found change the order of conditions
if (any(conditionsFound)) {
temp <- condition1
condition1 <- condition2
condition2 <- temp
} else {
stop(
paste(
'The wanted comparison: \'',
condition1,
' vs ',
condition2,
'\' is not in the data - please revise accordingly'
)
)
}
}
} else {
if( is.null(condition1) & is.null(condition2)) {
condition1 <- allConditionPairs$condition_1
condition2 <- allConditionPairs$condition_2
}
levelsToMatch <- c(condition1, condition2)
}
}
}
### Modify input (interpret input)
if (TRUE) {
### Handle gene and isoform_id input
if (!is.null(gene)) {
# Decode gene supplied
if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_id)
) {
gene_id <- gene
isoform_id <-
unique(switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in% gene_id
)])
} else if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_name)
) {
gene_id <-
unique(switchAnalyzeRlist$isoformFeatures$gene_id[which(
tolower(
switchAnalyzeRlist$isoformFeatures$gene_name
) %in% tolower(gene)
)])
if (length(gene_id) > 1) {
stop(
paste(
'The gene supplied covers multiple gene_ids (usually due to gene duplications). Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
isoform_id <-
unique(
switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in%
gene_id
)])
} else {
similarGenes <- c(
unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_id
)
)]
),
unique(
switchAnalyzeRlist$isoformFeatures$gene_name[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_name
)
)]
)
)
if (length(similarGenes)) {
stop(
paste(
'The gene supplied is not pressent in the switchAnalyzeRlist. did you mean any of: \'',
paste(similarGenes, collapse = '\', \''),
'\'',
sep = ''
)
)
} else {
stop(
'The gene supplied is not pressent in the switchAnalyzeRlist, please re-check the name and try again.'
)
}
}
if (!length(isoform_id)) {
stop(
'No isoforms annotated to the supplied gene was found. re-check the name and try again.'
)
}
} else {
if (any(
isoform_id %in%
switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
if ( !all(
isoform_id %in%
switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
notFound <-
setdiff(isoform_id,
switchAnalyzeRlist$isoformFeatures$isoform_id)
warning(
paste(
'\nThe following isoform was not found: \'',
paste(notFound, collapse = '\', \''),
'\'. Only the other isoforms will be used\n',
sep = ''
)
)
}
gene_id <- unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id
)]
)
if (length(gene_id) > 1) {
stop(
paste(
'The isoforms supplied covers multiple gene_ids. Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
} else {
stop(
'Non of the supplied isoforms were found in the switchAnalyzeRlist, please re-check the name and try again'
)
}
}
### Look into number of characters
analyzeStrandCompositionInWhiteSpaces <-
function(aString) {
# aString <- 'Ab1'
round(sum( sapply(
strsplit(aString, '')[[1]],
function(aCharacter) {
# Test if whitespace
if (aCharacter == ' ') {
return(1)
}
# Test if number
if (!is.na(suppressWarnings(as.integer(aCharacter)))) {
return(2) # whitespace pr number
}
# test symbols
if (aCharacter == '_') {
return(2) # whitespace pr character
}
# test symbols
if (aCharacter == '.') {
return(1) # whitespace pr numbers
}
# test upper
if (aCharacter == toupper(aCharacter)) {
return(2.4) # whitespace pr uppercase
}
# else it is probably lower
return(1.8) # whitespace pr lowercase
}
) ))
}
maxNrCharacters <- max(
c(
analyzeStrandCompositionInWhiteSpaces(isoform_id),
analyzeStrandCompositionInWhiteSpaces(condition1),
analyzeStrandCompositionInWhiteSpaces(condition2)
)
)
modifyNames <- function(aVec, extendToLength) {
aVec <- as.character(aVec)
tmp <- sapply(aVec, function(x) {
currentLength <- analyzeStrandCompositionInWhiteSpaces(x)
whitespacesToAdd <-
round(extendToLength - currentLength - 1)
if (whitespacesToAdd > 0) {
x <-
paste(x, paste(rep(
' ', whitespacesToAdd
), collapse = ''), collapse = '')
}
return(x)
})
names(tmp) <- NULL
return(tmp)
}
### mofify theme to rotate x axis labels
localTheme$axis.text.x$angle <- -35
localTheme$axis.text.x$hjust <- 0
localTheme$axis.text.x$vjust <- 1
### Helper function
trimWhiteSpace <- function (x) {
gsub("^\\s+|\\s+$", "", x)
}
### Extract gene name
if( 'gene_name' %in% colnames(switchAnalyzeRlist$isoformFeatures) ) {
gene_name <- switchAnalyzeRlist$isoformFeatures$gene_name[match(
gene_id, switchAnalyzeRlist$isoformFeatures$gene_id
)]
} else {
gene_name <- gene_id
}
}
### Extract and make plots
if (TRUE) {
### Common for all
if (TRUE) {
### Make list to store plots
plotList <- list()
extendFactor <- 1 + extendFactor
# helper function
evalSig <- function(pValue, alphas) {
sapply(pValue, function(x) {
if (is.na(x)) {
return('NA')
} else if (x < min(alphas)) {
sigLevel <- '***'
} else if (x < max(alphas)) {
sigLevel <- '*'
} else {
sigLevel <- 'ns'
}
return(sigLevel)
})
}
### Subset to contributing genes
columnsToExtract <-
c(
'isoform_id',
'condition_1',
'condition_2',
'IF1',
'IF2',
'isoform_switch_q_value'
)
isoformUsage <-
unique(switchAnalyzeRlist$isoformFeatures[which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id &
switchAnalyzeRlist$isoformFeatures$condition_1 ==
condition1 &
switchAnalyzeRlist$isoformFeatures$condition_2 ==
condition2
) , columnsToExtract])
if (nrow(isoformUsage) < 1) {
stop(
'The chosen combination of gene/isoforms and conditions are not annoatated in the switchAnalyzeRlist'
)
}
isoformUsage <-
isoformUsage[which(isoformUsage$IF1 > IFcutoff |
isoformUsage$IF2 > IFcutoff), ]
if (nrow(isoformUsage) < 1) {
stop('No isoforms were left after the \'isoformUsage\' filter was applied')
}
isoform_id <-
intersect(isoform_id, isoformUsage$isoform_id)
# Interesting rows - common for gene and isoforms
rowsToExtract <- which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id &
switchAnalyzeRlist$isoformFeatures$condition_1 ==
condition1 &
switchAnalyzeRlist$isoformFeatures$condition_2 ==
condition2
)
### Condition char
### Extract size of condition lavel
allLabels <- c( condition1, condition2 )
if ('domainAnalysis' %in% names(switchAnalyzeRlist)) {
localDomains <-
switchAnalyzeRlist$domainAnalysis[
which(
switchAnalyzeRlist$domainAnalysis$isoform_id
%in% isoform_id
),
c('isoform_id', 'hmm_name')
]
domianList <-
split(
localDomains$hmm_name,
f = localDomains$isoform_id
)
domainNames <-
unique(unlist(lapply(domianList, function(aVec) {
nameTable <- as.data.frame(
table(aVec), stringsAsFactors = FALSE
)
# only modify those with mutiple instances
nameTable$newName <- nameTable$aVec
modifyIndex <- which(nameTable$Freq > 1)
nameTable$newName[modifyIndex] <-
paste(nameTable$aVec[modifyIndex],
' (x',
nameTable$Freq[modifyIndex],
')',
sep = '')
newVec <-
nameTable$newName[match(aVec, nameTable$aVec)]
return(newVec)
})))
allLabels <- c(allLabels, domainNames)
}
if ('idrAnalysis' %in% names(switchAnalyzeRlist)) {
localIdrs <-
switchAnalyzeRlist$idrAnalysis[
which(
switchAnalyzeRlist$idrAnalysis$isoform_id
%in% isoform_id
),
c('isoform_id', 'idr_type')
]
idrList <-
split(
localIdrs$idr_type,
f = localIdrs$isoform_id
)
idrNames <-
unique(unlist(lapply(idrList, function(aVec) {
nameTable <- as.data.frame(
table(aVec), stringsAsFactors = FALSE
)
# only modify those with mutiple instances
nameTable$newName <- nameTable$aVec
modifyIndex <- which(nameTable$Freq > 1)
nameTable$newName[modifyIndex] <-
paste(nameTable$aVec[modifyIndex],
' (x',
nameTable$Freq[modifyIndex],
')',
sep = '')
newVec <-
nameTable$newName[match(aVec, nameTable$aVec)]
return(newVec)
})))
allLabels <- c(allLabels, idrNames)
}
if ('signalPeptideAnalysis' %in% names(switchAnalyzeRlist)) {
if (any(
isoform_id %in%
switchAnalyzeRlist$signalPeptideAnalysis$isoform_id
)) {
allLabels <- c(allLabels, 'Signal Peptide')
}
}
conditionMaxCharacter <-
max(c(
sapply(
allLabels,
analyzeStrandCompositionInWhiteSpaces
),
50
))
}
# Gene expression
if (TRUE) {
### Extract relevant data
columnsToExtract <-
c(
'condition_1',
'condition_2',
'gene_value_1',
'gene_value_2',
'gene_stderr_1',
'gene_stderr_2',
'gene_q_value'
)
geneExpression <-
as.data.frame(unique(switchAnalyzeRlist$isoformFeatures[
rowsToExtract,
columnsToExtract
]))
if (optimizeForCombinedPlot) {
geneExpression$condition_1 <-
modifyNames(aVec = geneExpression$condition_1,
extendToLength = maxNrCharacters)
geneExpression$condition_2 <-
modifyNames(aVec = geneExpression$condition_2,
extendToLength = maxNrCharacters)
}
### Massage expression
geneExpression1 <-
geneExpression[, c(
'condition_1', 'gene_value_1', 'gene_stderr_1'
)]
geneExpression2 <-
geneExpression[, c(
'condition_2', 'gene_value_2', 'gene_stderr_2'
)]
colnames(geneExpression1) <-
colnames(geneExpression2) <-
c('Condition', 'gene_expression', 'stderr')
geneExpressionCombined <-
rbind(geneExpression1, geneExpression2)
### Calculate CI and extract confidence level
if (addErrorbars) {
# add replicateNumber
repNrs <-
switchAnalyzeRlist$condition[which(
switchAnalyzeRlist$conditions$condition %in%
c(condition1, condition2)
), ]
if (optimizeForCombinedPlot) {
repNrs$condition <-
modifyNames(
repNrs$condition,
extendToLength = maxNrCharacters
)
}
geneExpressionCombined <-
merge(geneExpressionCombined,
repNrs,
by.x = 'Condition',
by.y = 'condition')
# calculate CI
if (confidenceIntervalErrorbars) {
#geneExpressionCombined$CI <- geneExpressionCombined$stderr * qt(confidenceInterval/2 + .5, geneExpressionCombined$nrReplicates-1)
geneExpressionCombined$CI <-
geneExpressionCombined$stderr *
qnorm(confidenceInterval / 2 + .5)
} else {
geneExpressionCombined$CI <- geneExpressionCombined$stderr
}
geneExpressionCombined$CI_up <-
geneExpressionCombined$gene_expression +
geneExpressionCombined$CI
geneExpressionCombined$CI_down <-
sapply(geneExpressionCombined$gene_expression -
geneExpressionCombined$CI, function(x)
max(c(0, x)))
### Evalueate signifiance
sigLevelDF <- data.frame(
sigLevel = evalSig(geneExpression$gene_q_value, alphas),
sigLevelPos = max(
c(
geneExpressionCombined$gene_expression,
geneExpressionCombined$CI_up,
geneExpressionCombined$CI_down
),
na.rm = TRUE
) * (extendFactor),
stringsAsFactors = FALSE
)
if (any(is.na(sigLevelDF$sigLevelPos))) {
sigLevelDF$sigLevelPos[which(
is.na(sigLevelDF$sigLevelPos)
)] <- 0
}
} else {
sigLevelDF <- data.frame(
sigLevel = evalSig(geneExpression$gene_q_value, alphas),
sigLevelPos = max(geneExpressionCombined$gene_expression) *
(extendFactor),
stringsAsFactors = FALSE
)
}
# calculate new y axis
additionFactor <- as.integer(logYaxis)
yMax <-
max(sigLevelDF$sigLevelPos + additionFactor) * 1.1
ymin <- 0 + additionFactor
### Remove NA sig level
sigLevelDF <-
sigLevelDF[which(sigLevelDF$sigLevel != 'NA'), ]
#sigLevelDF$sigLevelPos <- sigLevelDF$sigLevelPos + additionFactor
sigAnnot <- nrow(sigLevelDF) != 0
geneExpressionCombined$Analyis <- 'Gene Expression'
### Add levels
geneExpressionCombined$Condition <- factor(
geneExpressionCombined$Condition,
levels = geneExpressionCombined$Condition[sapply(
levelsToMatch, function(x) {
which(grepl(
paste0('^',x,'$'),
trimWhiteSpace(geneExpressionCombined$Condition)
))[1]
}
)]
)
### Build Plot
g1 <-
ggplot(data = geneExpressionCombined, aes(x = Condition))
if( optimizeForCombinedPlot ) {
g1 <- g1 +
geom_bar(
aes(y = gene_expression + additionFactor, fill = Condition),
stat = "identity",
position = 'dodge'
)
} else {
g1 <- g1 +
geom_bar(
aes(y = gene_expression + additionFactor),
stat = "identity",
position = 'dodge'
)
}
# errorbar
if (addErrorbars) {
g1 <-
g1 + geom_errorbar(
aes(
ymax = CI_up + additionFactor,
ymin = CI_down + additionFactor
),
width = 0.2
)
}
# sig indication
if (sigAnnot) {
g1 <- g1 +
geom_segment(
data = sigLevelDF,
aes(
x = 1,
xend = 2,
y = sigLevelPos + additionFactor,
yend = sigLevelPos + additionFactor
)
) +
geom_text(
data = sigLevelDF,
aes(
x = 1.5,
y = sigLevelPos + additionFactor,
label = sigLevel
),
vjust = -0.2,
size = localTheme$text$size * 0.3
)
}
# add the rest
g1 <- g1 +
localTheme + # modify to rotate labels
theme(strip.background = element_rect(
fill = "white",
size = 0.5)
)
if( optimizeForCombinedPlot ) {
g1 <- g1 +
scale_fill_manual(values = c('darkgrey', '#333333')) +
guides(fill="none")
}
if (logYaxis) {
g1 <- g1 + scale_y_log10() +
coord_cartesian(ylim = c(ymin+1, yMax))
} else {
g1 <- g1 + coord_cartesian(ylim = c(ymin, yMax))
}
if( ! optimizeForCombinedPlot ) {
g1 <- g1 +
labs(x = 'Condition', y = 'Gene Expression', title = paste0('Expression of ', gene_name))
} else {
g1 <- g1 +
facet_wrap( ~ Analyis, ncol = 1) +
labs(x = 'Condition', y = 'Gene Expression')
}
### add to list
plotList[['gene_expression']] <- g1
}
# Isoforms
if (TRUE) {
# Extract relevant data
columnsToExtract <-
c(
'isoform_id',
'condition_1',
'condition_2',
'iso_value_1',
'iso_value_2',
'iso_stderr_1',
'iso_stderr_2',
'iso_q_value'
)
isoExpression <-
unique(switchAnalyzeRlist$isoformFeatures[
rowsToExtract,
columnsToExtract
])
repNrs <- switchAnalyzeRlist$condition
if (optimizeForCombinedPlot) {
# Change isoform ids
isoExpression$isoform_id <-
modifyNames(aVec = isoExpression$isoform_id,
extendToLength = maxNrCharacters)
isoExpression$condition_1 <-
modifyNames(aVec = isoExpression$condition_1,
extendToLength = conditionMaxCharacter)
isoExpression$condition_2 <-
modifyNames(aVec = isoExpression$condition_2,
extendToLength = conditionMaxCharacter)
repNrs$condition <-
modifyNames(aVec = repNrs$condition,
extendToLength = conditionMaxCharacter)
}
### Massage data
isoExpression2 <-
reshape2::melt(
isoExpression[, c(
'isoform_id', 'iso_value_1', 'iso_value_2'
)],
id.vars = 'isoform_id'
)
colnames(isoExpression2)[3] <- 'expression'
isoExpression2$Condition <- isoExpression$condition_1
isoExpression2$Condition[which(
grepl('_2$', isoExpression2$variable)
)] <- isoExpression$condition_2
isoExpression2 <- isoExpression2[, -2]
isoStderr <-
reshape2::melt(
isoExpression[, c(
'isoform_id', 'iso_stderr_1', 'iso_stderr_2'
)],
id.vars = 'isoform_id'
)
colnames(isoStderr)[3] <- 'stderr'
isoStderr$Condition <- isoExpression$condition_1
isoStderr$Condition[which(grepl('_2$', isoStderr$variable))] <-
isoExpression$condition_2
isoStderr <- isoStderr[, -2]
isoExpressionCombined <-
merge(isoExpression2,
isoStderr,
by = c('isoform_id', 'Condition'))
### Add CI
if (addErrorbars) {
isoExpressionCombined <-
merge(isoExpressionCombined,
repNrs,
by.x = 'Condition',
by.y = 'condition')
# calculate CI
if (confidenceIntervalErrorbars) {
#isoExpressionCombined$CI <- isoExpressionCombined$stderr * qt(confidenceInterval/2 + .5, isoExpressionCombined$nrReplicates-1)
isoExpressionCombined$CI <-
isoExpressionCombined$stderr *
qnorm(confidenceInterval / 2 + .5)
} else {
isoExpressionCombined$CI <- isoExpressionCombined$stderr
}
isoExpressionCombined$CI_hi <-
isoExpressionCombined$expression + isoExpressionCombined$CI
isoExpressionCombined$CI_low <-
sapply(
isoExpressionCombined$expression -
isoExpressionCombined$CI,
function(x) {
max(c(0, x))
}
)
}
isoExpressionCombined$Analyis <- 'Isoform Expression'
### prepare significance
sigDF <- isoExpression[, c('isoform_id', 'iso_q_value')]
sigDF$sigEval <- evalSig(sigDF$iso_q_value, alphas)
sigDF2 <-
plyr::ddply(
sigDF,
.variables = 'isoform_id',
.fun = function(aDF) {
correspondingExpData <-
isoExpressionCombined[which(
isoExpressionCombined$isoform_id ==
aDF$isoform_id
), ]
if (addErrorbars) {
aDF$ymax <-
max(
c(
correspondingExpData$expression,
correspondingExpData$expression +
correspondingExpData$CI
),
na.rm = TRUE
)
} else {
aDF$ymax <- max(correspondingExpData$expression)
}
return(aDF)
}
)
sigDF2$ymax <-
sigDF2$ymax + max(sigDF2$ymax) * (extendFactor - 1)
sigDF2$isoform_id <- factor(sigDF2$isoform_id)
sigDF2$idNr <- as.numeric(sigDF2$isoform_id)
if (any(is.na(sigDF2$ymax))) {
sigDF2$ymax[which(is.na(sigDF2$ymax))] <- 0
}
additionFactor <- as.integer(logYaxis)
yMax <- max(sigDF2$ymax + additionFactor) * 1.1
ymin <- 0 + additionFactor
### Remove NA sig level
sigDF2 <- sigDF2[which(!is.na(sigDF2$iso_q_value)), ]
sigAnnot <- nrow(sigDF2) != 0
### Add levels
isoExpressionCombined$Condition <- factor(
isoExpressionCombined$Condition,
levels = isoExpressionCombined$Condition[
sapply(
levelsToMatch,
function(x) {
which(grepl(
paste0('^',x,'$'),
trimWhiteSpace(isoExpressionCombined$Condition)
))[1]
}
)
]
)
### Buil plot
g2 <-
ggplot(data = isoExpressionCombined, aes(x = isoform_id)) +
geom_bar(
aes(y = expression + additionFactor, fill = Condition),
stat = "identity",
position = 'dodge'
)
# errorbar
if (addErrorbars) {
g2 <- g2 +
geom_errorbar(
aes(
ymax = CI_hi + additionFactor,
ymin = CI_low + additionFactor,
group = Condition
),
position = position_dodge(width = 0.9),
width = 0.2
)
}
if (sigAnnot) {
g2 <- g2 +
geom_text(
data = sigDF2,
aes(
y = ymax + additionFactor,
label = sigEval
),
vjust = -0.2,
size = localTheme$text$size * 0.3
) +
geom_segment(
data = sigDF2,
aes(
x = idNr - 0.25,
xend = idNr + 0.25,
y = ymax + additionFactor,
yend = ymax + additionFactor
)
)
}
g2 <- g2 +
scale_fill_manual(values = c('darkgrey', '#333333')) +
labs(x = 'Isoform', y = 'Isoform Expression') +
localTheme + # modify to tilt conditions
theme(strip.background = element_rect(
fill = "white",
size = 0.5
))
if (logYaxis) {
g2 <- g2 + scale_y_log10() +
coord_cartesian(ylim = c(ymin+1, yMax))
} else {
g2 <- g2 + coord_cartesian(ylim = c(ymin, yMax))
}
if( ! optimizeForCombinedPlot ) {
g2 <- g2 + labs(x = 'Isoform', y = 'Isoform Expression', title = paste0('Isoform Expression in ', gene_name))
} else {
g2 <- g2 +
facet_wrap( ~ Analyis, ncol = 1) +
labs(x = 'Isoform', y = 'Isoform Expression')
}
### add to list
plotList[['isoform_expression']] <- g2
}
# Isoform usage
if (TRUE) {
if (optimizeForCombinedPlot) {
isoformUsage$condition_1 <-
modifyNames(aVec = isoformUsage$condition_1,
extendToLength = conditionMaxCharacter)
isoformUsage$condition_2 <-
modifyNames(aVec = isoformUsage$condition_2,
extendToLength = conditionMaxCharacter)
isoformUsage$isoform_id <-
modifyNames(aVec = isoformUsage$isoform_id,
extendToLength = maxNrCharacters)
}
### Massage data
isoformUsage2 <-
reshape2::melt(
isoformUsage[, c('isoform_id', 'IF1', 'IF2')],
id.vars = 'isoform_id'
)
colnames(isoformUsage2)[3] <- 'IF'
isoformUsage2$Condition <- isoformUsage$condition_1
isoformUsage2$Condition[which(
grepl('2$', isoformUsage2$variable)
)] <- isoformUsage$condition_2
isoformUsage2 <- isoformUsage2[, -2]
isoformUsage2$Analyis <- 'Isoform Usage'
### prepare significance
sigDF <-
isoformUsage[, c('isoform_id', 'isoform_switch_q_value')]
sigDF$sigEval <-
evalSig(pValue = sigDF$isoform_switch_q_value,
alphas = alphas)
sigDF2 <-
plyr::ddply(
sigDF,
.variables = 'isoform_id',
.fun = function(aDF) {
correspondingExpData <-
isoformUsage2[which(
isoformUsage2$isoform_id == aDF$isoform_id
), ]
aDF$ymax <- max(correspondingExpData$IF, na.rm = TRUE)
return(aDF)
}
)
sigDF2$ymax <-
sigDF2$ymax + max(sigDF2$ymax) * (extendFactor - 1)
sigDF2$isoform_id <- factor(sigDF2$isoform_id)
sigDF2$idNr <- as.numeric(sigDF2$isoform_id)
### Add levels
isoformUsage2$Condition <- factor(
isoformUsage2$Condition,
levels = isoformUsage2$Condition[
sapply(
levelsToMatch,
function(x){
which(grepl(
paste0('^',x,'$'),
trimWhiteSpace(isoformUsage2$Condition)
))[1]
}
)
]
)
yMax <- max(sigDF2$ymax) * 1.1
### Remove NA sig level
sigDF2 <-
sigDF2[which(!is.na(sigDF2$isoform_switch_q_value)), ]
sigAnnot <- nrow(sigDF2) != 0
### Plot it
g3 <- ggplot(data = isoformUsage2, aes(x = isoform_id)) +
geom_bar(aes(y = IF, fill = Condition),
stat = "identity",
position = 'dodge')
# annot
if (sigAnnot) {
g3 <- g3 +
geom_text(
data = sigDF2,
aes(y = ymax, label = sigEval),
vjust = -0.2,
size = localTheme$text$size * 0.3
) +
geom_segment(data = sigDF2,
aes(
x = idNr - 0.25,
xend = idNr + 0.25,
y = ymax,
yend = ymax
)) +
coord_cartesian(ylim = c(0, yMax))
}
g3 <- g3 +
scale_fill_manual(values = c('darkgrey', '#333333')) +
localTheme + # modify to tilt conditions
theme(strip.background = element_rect(
fill = "white",
size = 0.5)
)
if( ! optimizeForCombinedPlot ) {
g3 <- g3 +
labs(x = 'Isoform', y = 'Isoform Fraction (IF)', title = paste0('Isoform Usage in ', gene_name))
} else {
g3 <- g3 +
facet_wrap( ~ Analyis, ncol = 1) +
labs(x = 'Isoform', y = 'Isoform Fraction (IF)')
}
plotList[['isoform_usage']] <- g3
}
}
### Add isoforms analyzed
plotList$isoformsAnalyzed <- isoform_id
### Return result
return(plotList)
}
switchPlot <- function(
### Core arguments
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
condition1,
condition2,
### Advanced arguments
IFcutoff = 0.05,
dIFcutoff = 0.1,
alphas = c(0.05, 0.001),
rescaleTranscripts = TRUE,
plotTopology = TRUE,
reverseMinus = TRUE,
addErrorbars = TRUE,
logYaxis = FALSE,
localTheme = theme_bw(base_size = 8),
additionalArguments = list()
) {
### Test Input
if (TRUE) {
# check switchAnalyzeRlist
if (class(switchAnalyzeRlist) != 'switchAnalyzeRlist') {
stop(
'The object supplied to \'switchAnalyzeRlist\' is not a \'switchAnalyzeRlist\''
)
}
if( switchAnalyzeRlist$sourceId == 'preDefinedSwitches' ) {
stop(
paste(
'The switchAnalyzeRlist is made from pre-defined isoform switches',
'which means it is made without defining conditions (as it should be).',
'\nTherefore a switchPlot cannot be made. Use switchPlotTranscript() instead.',
sep = ' '
)
)
}
if (all(is.na(
switchAnalyzeRlist$isoformFeatures$gene_switch_q_value
))) {
warning(
'We recomend running the isoform switching analysis before doing the transcript plot. See ?detectIsoformSwitching for more details'
)
}
# check isoform and gene name input
idInfoCheck <- sum(c(is.null(gene), is.null(isoform_id)))
if (idInfoCheck != 1) {
if (idInfoCheck == 0) {
stop('One of \'gene\' or \'isoform_id\' must be given as input')
}
if (idInfoCheck == 2) {
stop('Only one of \'gene\' or \'isoform_id\' can be supplied')
}
}
# chech conditions
if (TRUE) {
### Identify conditions
allConditionPairs <-
unique(switchAnalyzeRlist$isoformFeatures[,c(
'condition_1', 'condition_2'
)])
levelsToMatch <- as.vector(t(allConditionPairs))
if (nrow(allConditionPairs) > 1) {
if (missing(condition1) | missing(condition2)) {
stop(
'Both the \'condition1\' and \'condition2\' arguments must be supplied (when there is more than two comparisons)'
)
}
if (is.null(switchAnalyzeRlist$conditions)) {
stop(
'Please make sure the switchAnalyzeRlist is properly constructed - it is missing the \'condition\' argument'
)
}
if (!all(
c(condition1, condition2) %in%
switchAnalyzeRlist$conditions$condition
)) {
stop(
paste(
'Both condition arguments must be eith of: \'',
paste(
switchAnalyzeRlist$conditions$condition,
collapse = '\', \''
),
'\'',
sep = ''
)
)
}
if (condition1 == condition2) {
stop(
'The \'condition1\' and \'condition2\' arguments must be different'
)
}
conditionsFound <-
apply(allConditionPairs, 1, function(x) {
x[1] == condition1 & x[2] == condition2
})
if (!any(conditionsFound)) {
# the the conditions are not found try revers order
conditionsFound <-
apply(allConditionPairs, 1, function(x) {
x[2] == condition1 & x[1] == condition2
})
# if now found change the order of conditions
if (any(conditionsFound)) {
temp <- condition1
condition1 <- condition2
condition2 <- temp
} else {
stop(
paste(
'The wanted comparison: \'',
condition1,
' vs ',
condition2,
'\' is not in the data - please revise accordingly'
)
)
}
}
} else {
condition1 <- allConditionPairs$condition_1
condition2 <- allConditionPairs$condition_2
}
levelsToMatch <-
levelsToMatch[which(
levelsToMatch %in% c(condition1, condition2)
)]
}
}
### Parse additional list argument
if (TRUE) {
### Expression plot arguments
if (TRUE) {
## Make list with default values - can be replaced by as.list(args(expressionPlots)) ?
eArgList <- list(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
isoform_id = isoform_id,
condition1 = condition1,
condition2 = condition2,
IFcutoff = IFcutoff,
addErrorbars = addErrorbars,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
#alphas = c(0.05, 0.001),
alphas = alphas,
logYaxis = logYaxis,
extendFactor = 0.05,
localTheme = localTheme
)
### Modify default arguments if nessesary
# subset to only those not already covered by the arguments
additionalArguments2 <-
additionalArguments[which(
names(additionalArguments) %in% c(
'confidenceIntervalErrorbars',
'confidenceInterval',
'alphas',
'extendFactor',
'rescaleRoot'
)
)]
if (length(additionalArguments2) != 0) {
newArgNames <- names(additionalArguments2)
for (i in seq_along(additionalArguments2)) {
eArgList[[newArgNames[i]]] <- additionalArguments2[[i]]
}
}
}
### Transcript plot arguments
if (TRUE) {
## Make list with default values - can be replaced by as.list(args(expressionPlots)) ?
tArgList <- list(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
isoform_id = isoform_id,
rescaleTranscripts = rescaleTranscripts,
plotTopology = plotTopology,
rescaleRoot = 3,
plotXaxis = !rescaleTranscripts,
reverseMinus = reverseMinus,
ifMultipleIdenticalAnnotation = 'summarize',
rectHegith = 0.2,
codingWidthFactor = 2,
nrArrows = 20,
arrowSize = 0.2,
localTheme = localTheme,
plot = TRUE
)
### Modify default arguments if nessesary
# subset to only those not already covered by the arguments
additionalArguments2 <-
additionalArguments[which(
names(additionalArguments) %in% c(
'ifMultipleIdenticalAnnotation',
'rectHegith',
'codingWidthFactor',
'nrArrows',
'arrowSize',
'rescaleRoot'
)
)]
if (length(additionalArguments2) != 0) {
newArgNames <- names(additionalArguments2)
for (i in seq_along(additionalArguments2)) {
tArgList[[newArgNames[i]]] <- additionalArguments2[[i]]
}
}
}
}
### Make subplots - these functions also check the input thoroughly
if (TRUE) {
# expression plots
expressionPlots <- expressionAnalysisPlot(
switchAnalyzeRlist = eArgList$switchAnalyzeRlist,
gene = eArgList$gene,
isoform_id = eArgList$isoform_id,
condition1 = eArgList$condition1,
condition2 = eArgList$condition2,
IFcutoff = eArgList$IFcutoff,
addErrorbars = eArgList$addErrorbars,
confidenceIntervalErrorbars = eArgList$confidenceIntervalErrorbars,
confidenceInterval = eArgList$confidenceInterval,
alphas = eArgList$alphas,
optimizeForCombinedPlot = TRUE,
logYaxis = eArgList$logYaxis,
extendFactor = eArgList$extendFactor,
localTheme = eArgList$localTheme
)
# transcript plots
transcriptPlot <- switchPlotTranscript(
switchAnalyzeRlist = tArgList$switchAnalyzeRlist,
gene = NULL,
# Ensures only isoforms passing IFcutoff are plotted
isoform_id = expressionPlots$isoformsAnalyzed,
# Ensures only isoforms passing IFcutoff are plotted
rescaleTranscripts = tArgList$rescaleTranscripts,
plotTopology = tArgList$plotTopology,
rescaleRoot = tArgList$rescaleRoot,
plotXaxis = tArgList$plotXaxis,
reverseMinus = tArgList$reverseMinus,
ifMultipleIdenticalAnnotation = tArgList$ifMultipleIdenticalAnnotation,
rectHegith = tArgList$rectHegith,
codingWidthFactor = tArgList$codingWidthFactor,
nrArrows = tArgList$nrArrows,
arrowSize = tArgList$arrowSize,
optimizeForCombinedPlot = TRUE,
condition1 = condition1,
condition2 = condition2,
dIFcutoff = dIFcutoff,
IFcutoff = IFcutoff,
localTheme = localTheme
)
}
### Handle gene and isoform_id input
if (TRUE) {
### Handle gene and isoform_id input
if (!is.null(gene)) {
# Decode gene supplied
if (
tolower(gene) %in% tolower(
switchAnalyzeRlist$isoformFeatures$gene_id
)
) {
gene_id <- gene
isoform_id <-
unique(switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in% gene_id
)])
} else if (
tolower(gene) %in%
tolower(switchAnalyzeRlist$isoformFeatures$gene_name)
) {
gene_id <-
unique(switchAnalyzeRlist$isoformFeatures$gene_id[which(
tolower(
switchAnalyzeRlist$isoformFeatures$gene_name
) %in% tolower(gene)
)])
if (length(gene_id) > 1) {
stop(
paste(
'The gene supplied covers multiple gene_ids (usually due to gene duplications). Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
isoform_id <-
unique(switchAnalyzeRlist$isoformFeatures$isoform_id[which(
switchAnalyzeRlist$isoformFeatures$gene_id %in% gene_id
)])
} else {
similarGenes <- c(
unique(
switchAnalyzeRlist$isoformFeatures$gene_id[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_id
)
)]
),
unique(
switchAnalyzeRlist$isoformFeatures$gene_name[which(
agrepl(
gene,
switchAnalyzeRlist$isoformFeatures$gene_name
)
)]
)
)
if (length(similarGenes)) {
stop(
paste(
'The gene supplied is not pressent in the switchAnalyzeRlist. did you mean any of: \'',
paste(similarGenes, collapse = '\', \''),
'\'',
sep = ''
)
)
} else {
stop(
'The gene supplied is not pressent in the switchAnalyzeRlist, please re-check the name and try again.'
)
}
}
if (!length(isoform_id)) {
stop(
'No isoforms annotated to the supplied gene was found. re-check the name and try again.'
)
}
} else {
if (any(
isoform_id %in% switchAnalyzeRlist$isoformFeatures$isoform_id
)) {
if (! all(isoform_id %in%
switchAnalyzeRlist$isoformFeatures$isoform_id)
) {
notFound <-
setdiff(isoform_id,
switchAnalyzeRlist$isoformFeatures$isoform_id)
warning(
paste(
'\nThe following isoform was not found: \'',
paste(notFound, collapse = '\', \''),
'\'. Only the other isoforms will be used\n',
sep = ''
)
)
}
gene_id <-
unique(switchAnalyzeRlist$isoformFeatures$gene_id[which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in%
isoform_id
)])
if (length(gene_id) > 1) {
stop(
paste(
'The isoforms supplied covers multiple gene_ids. Currently multigene plotting is not supported. Please use either of the following gene_ids: \'',
paste(gene_id, collapse = '\', \''),
'\', and try again',
sep = ''
)
)
}
} else {
stop(
'Non of the supplied isoforms were found in the switchAnalyzeRlist, please re-check the name and try again'
)
}
}
}
### Subset to isoforms passing IFcutoff filter
isoform_id <-
intersect(isoform_id, expressionPlots$isoformsAnalyzed)
### Extract gene name
indexToAnalyze <-
which(switchAnalyzeRlist$isoformFeatures$isoform_id %in% isoform_id)
geneName <-
paste(
unique(
switchAnalyzeRlist$isoformFeatures$gene_name[indexToAnalyze]
),
collapse = ','
)
if (geneName == 'NA') {
geneName <- 'unannotated gene'
}
### Extract Index with ORF
isoform_id2 <- isoform_id[which(
! is.na( switchAnalyzeRlist$orfAnalysis$orfTransciptStart[match( isoform_id, switchAnalyzeRlist$orfAnalysis$isoform_id)] )
)]
indexToAnalyze2 <-
which(
switchAnalyzeRlist$isoformFeatures$isoform_id %in% isoform_id2
)
### are domains analysed
if (any(
c('domain_identified', 'signal_peptide_identified','idr_identified') %in%
colnames(switchAnalyzeRlist$isoformFeatures)
)) {
anyDomains <-
any(
switchAnalyzeRlist$isoformFeatures$domain_identified[
indexToAnalyze2
] == 'yes'
) |
any(
switchAnalyzeRlist$isoformFeatures$signal_peptide_identified[
indexToAnalyze2
] == 'yes'
) |
any(
switchAnalyzeRlist$isoformFeatures$idr_identified[
indexToAnalyze2
] == 'yes'
)
if (is.na(anyDomains)) {
anyDomains <- FALSE
}
} else {
anyDomains <- FALSE
}
# Title
myTitle <- qplot(1:3, 1, geom = "blank") + theme(
panel.background = element_blank(),
line = element_blank(),
text = element_blank(),
plot.margin = margin(
t = 0,
r = 0,
b = 0,
l = 0,
unit = "cm"
)
) +
annotate(
geom = 'text',
x = 2,
y = 1,
size = localTheme$text$size * 0.6,
fontface = 'bold',
label = paste(
'The isoform switch in ',
geneName ,
' (' ,
condition1,
' vs ',
condition2,
')',
sep = ''
)
)
### Change plot margin
marginSize <- 0.3
expressionPlots2 <-
lapply(expressionPlots, function(x) {
x +
theme(
plot.margin = margin(
t = 0,
r = marginSize,
b = marginSize,
l = marginSize,
unit = "cm"
),
legend.position="none"
)
})
transcriptPlot2 <-
transcriptPlot + theme(
plot.margin = margin(
t = 0,
r = marginSize,
b = marginSize,
l = marginSize,
unit = "cm"
),
legend.position="none"
)
### Extract the legends and modify them to have equally long text strings
if (TRUE) {
### Extract the two legends
g_legend <- function(a.gplot) {
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <-
which(sapply(tmp$grobs, function(x)
x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
### Convert the legneds to ggplot2 via annotation_custom
if (anyDomains) {
tLegend <- g_legend(transcriptPlot)
transcriptLegend <-
qplot(1:10, 1:10, geom = "blank") + theme_bw() + theme(
line = element_blank(),
text = element_blank(),
panel.border = element_blank()
) +
annotation_custom(
tLegend ,
xmin = 0,
xmax = Inf,
ymin = -Inf,
ymax = Inf
) +
theme(
plot.margin = margin(
t = 0,
r = 0.5,
b = 0,
l = 0.5,
unit = "cm"
),
legend.margin = margin(
t = 0,
r = 0,
b = 0,
l = 0,
unit = "cm"
)
)
} else {
transcriptLegend <-
qplot(1:10, 1:10, geom = "blank") + theme_bw() + theme(
line = element_blank(),
text = element_blank(),
panel.border = element_blank()
)
}
eLegend <- g_legend(expressionPlots[[2]])
expressionLegend <-
qplot(1:10, 1:10, geom = "blank") + theme_bw() + theme(
line = element_blank(),
text = element_blank(),
panel.border = element_blank()
) +
annotation_custom(
eLegend ,
xmin = 0,
xmax = Inf,
ymin = 3,
ymax = 10
) +
theme(
plot.margin = margin(
t = 0,
r = 0.5,
b = 0,
l = 0.5,
unit = "cm"
),
legend.margin = margin(
t = 0,
r = 0,
b = 0,
l = 0,
unit = "cm"
)
)
}
### Plot everything together
plotAreaSize <- 10
legendSize <- 3
nColToUse <- plotAreaSize + legendSize
expPlotLast <- nColToUse - legendSize
lastTwoCols <- (nColToUse - legendSize + 1):nColToUse
# set up veiwport
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrow = 16, ncol = nColToUse)))
# print header
print(myTitle, vp = viewport(
layout.pos.row = 1,
layout.pos.col = 1:(nColToUse - legendSize)
))
# transctipt plot
suppressWarnings(print(
transcriptPlot2 + guides(fill = "none"),
vp = viewport(
layout.pos.row = 2:8,
layout.pos.col = 1:expPlotLast
)
))
### Expression legend
print(expressionLegend,
vp = viewport(layout.pos.row = 9:15, layout.pos.col = lastTwoCols))
# expression
print(
expressionPlots2$isoform_usage + guides(fill = "none"),
vp = viewport(
layout.pos.row = 9:15,
layout.pos.col = 7:expPlotLast
)
)
print(
expressionPlots2$isoform_expression + guides(fill = "none"),
vp = viewport(
layout.pos.row = 9:15,
layout.pos.col = 3:6
)
)
print(
expressionPlots2$gene_expression,
vp = viewport(
layout.pos.row = 9:15,
layout.pos.col = 1:2
)
)
# Transcript Legend
print(transcriptLegend,
vp = viewport(layout.pos.row = 2:8, layout.pos.col = lastTwoCols))
}
switchPlotGeneExp <- function(
switchAnalyzeRlist,
gene = NULL,
condition1 = NULL,
condition2 = NULL,
addErrorbars = TRUE,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
alphas = c(0.05, 0.001),
logYaxis = FALSE,
extendFactor = 0.05,
localTheme = theme_bw()
) {
expressionPlots <- expressionAnalysisPlot(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
condition1 = condition1,
condition2 = condition2,
addErrorbars = addErrorbars,
confidenceIntervalErrorbars = confidenceIntervalErrorbars,
confidenceInterval = confidenceInterval,
alphas = alphas,
extendFactor = extendFactor,
logYaxis = logYaxis,
localTheme = localTheme,
optimizeForCombinedPlot = FALSE
)
return(expressionPlots$gene_expression)
}
switchPlotIsoExp <- function(
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
condition1 = NULL,
condition2 = NULL,
IFcutoff = 0.05,
addErrorbars = TRUE,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
alphas = c(0.05, 0.001),
logYaxis = FALSE,
extendFactor = 0.05,
localTheme = theme_bw()
) {
expressionPlots <- expressionAnalysisPlot(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
isoform_id = isoform_id,
condition1 = condition1,
condition2 = condition2,
IFcutoff = IFcutoff,
addErrorbars = addErrorbars,
confidenceIntervalErrorbars = confidenceIntervalErrorbars,
confidenceInterval = confidenceInterval,
alphas = alphas,
extendFactor = extendFactor,
logYaxis = logYaxis,
localTheme = localTheme,
optimizeForCombinedPlot = FALSE
)
return(expressionPlots$isoform_expression)
}
switchPlotIsoUsage <- function(
switchAnalyzeRlist,
gene = NULL,
isoform_id = NULL,
condition1 = NULL,
condition2 = NULL,
IFcutoff = 0.05,
addErrorbars = TRUE,
confidenceIntervalErrorbars = TRUE,
confidenceInterval = 0.95,
alphas = c(0.05, 0.001),
extendFactor = 0.05,
localTheme = theme_bw()
) {
expressionPlots <- expressionAnalysisPlot(
switchAnalyzeRlist = switchAnalyzeRlist,
gene = gene,
isoform_id = isoform_id,
condition1 = condition1,
condition2 = condition2,
IFcutoff = IFcutoff,
addErrorbars = addErrorbars,
confidenceIntervalErrorbars = confidenceIntervalErrorbars,
confidenceInterval = confidenceInterval,
alphas = alphas,
extendFactor = extendFactor,
localTheme = localTheme,
optimizeForCombinedPlot = FALSE
)
return(expressionPlots$isoform_usage)
}
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