Nothing
## ----library------------------------------------------------------------------
library(specL)
## ----render, eval=FALSE-------------------------------------------------------
# library(rmarkdown)
# library(BiocStyle)
# report_file <- tempfile(fileext='.Rmd');
# file.copy(system.file("doc", "report.Rmd",
# package = "specL"),
# report_file);
# rmarkdown::render(report_file,
# output_format='html_document',
# output_file='/tmp/report_specL.html')
## ----defineInput--------------------------------------------------------------
if(!exists("INPUT")){
INPUT <- list(FASTA_FILE
= system.file("extdata", "SP201602-specL.fasta.gz",
package = "specL"),
BLIB_FILTERED_FILE
= system.file("extdata", "peptideStd.sqlite",
package = "specL"),
BLIB_REDUNDANT_FILE
= system.file("extdata", "peptideStd_redundant.sqlite",
package = "specL"),
MIN_IONS = 5,
MAX_IONS = 6,
MZ_ERROR = 0.05,
MASCOTSCORECUTOFF = 17,
FRAGMENTIONMZRANGE = c(300, 1250),
FRAGMENTIONRANGE = c(5, 200),
NORMRTPEPTIDES = specL::iRTpeptides,
OUTPUT_LIBRARY_FILE = tempfile(fileext ='.csv'),
RDATA_LIBRARY_FILE = tempfile(fileext ='.RData'),
ANNOTATE = TRUE
)
}
## ----cat, echo=FALSE, eval=FALSE----------------------------------------------
# cat(
# " MASCOTSCORECUTOFF = ", INPUT$MASCOTSCORECUTOFF, "\n",
# " BLIB_FILTERED_FILE = ", INPUT$BLIB_FILTERED_FILE, "\n",
# " BLIB_REDUNDANT_FILE = ", INPUT$BLIB_REDUNDANT_FILE, "\n",
# " MZ_ERROR = ", INPUT$MZ_ERROR, "\n",
# " FRAGMENTIONMZRANGE = ", INPUT$FRAGMENTIONMZRANGE, "\n",
# " FRAGMENTIONRANGE = ", INPUT$FRAGMENTIONRANGE, "\n",
# " FASTA_FILE = ", INPUT$FASTA_FILE, "\n",
# " MAX_IONS = ", INPUT$MAX_IONS, "\n",
# " MIN_IONS = ", INPUT$MIN_IONS, "\n"
# )
#
## ----kableParameter, echo=FALSE, results='asis'-------------------------------
library(knitr)
# kable(t(as.data.frame(INPUT)))
ii <- ((lapply(INPUT, function(x){ if(typeof(x) %in% c("character", "double")){paste(x, collapse = ', ')}else{NULL} } )))
parameter <- as.data.frame(unlist(ii))
names(parameter) <- 'parameter.values'
kable(parameter, caption = 'used INPUT parameter')
## ----defineFragmenIons--------------------------------------------------------
fragmentIonFunction_specL <- function (b, y) {
Hydrogen <- 1.007825
Oxygen <- 15.994915
Nitrogen <- 14.003074
b1_ <- (b )
y1_ <- (y )
b2_ <- (b + Hydrogen) / 2
y2_ <- (y + Hydrogen) / 2
return( cbind(b1_, y1_, b2_, y2_) )
}
## ----readSqliteFILTERED, warning=FALSE----------------------------------------
BLIB_FILTERED <- read.bibliospec(INPUT$BLIB_FILTERED_FILE)
summary(BLIB_FILTERED)
## ----readSqliteREDUNDANT, warning=FALSE---------------------------------------
BLIB_REDUNDANT <- read.bibliospec(INPUT$BLIB_REDUNDANT_FILE)
summary(BLIB_REDUNDANT)
## ----read.fasta---------------------------------------------------------------
if(INPUT$ANNOTATE){
FASTA <- read.fasta(INPUT$FASTA_FILE,
seqtype = "AA",
as.string = TRUE)
BLIB_FILTERED <- annotate.protein_id(BLIB_FILTERED,
fasta = FASTA)
}
## ----checkIRTs, echo=FALSE, results='asis'------------------------------------
library(knitr)
incl <- INPUT$NORMRTPEPTIDES$peptide %in% sapply(BLIB_REDUNDANT, function(x){x$peptideSequence})
INPUT$NORMRTPEPTIDES$included <- incl
if (sum(incl) > 0){
res <- INPUT$NORMRTPEPTIDES[order(INPUT$NORMRTPEPTIDES$rt),]
# row.names(res) <- 1:nrow(res)
kable(res, caption='peptides used for RT normaization.')
}
## ----specL::genSwathIonLib, message=FALSE-------------------------------------
specLibrary <- specL::genSwathIonLib(
data = BLIB_FILTERED,
data.fit = BLIB_REDUNDANT,
max.mZ.Da.error = INPUT$MZ_ERROR,
topN = INPUT$MAX_IONS,
fragmentIonMzRange = INPUT$FRAGMENTIONMZRANGE,
fragmentIonRange = INPUT$FRAGMENTIONRANGE,
fragmentIonFUN = fragmentIonFunction_specL,
mascotIonScoreCutOFF = INPUT$MASCOTSCORECUTOFF,
iRT = INPUT$NORMRTPEPTIDES
)
## ----summarySpecLibrary-------------------------------------------------------
summary(specLibrary)
## ----showSpecLibrary----------------------------------------------------------
# slotNames(specLibrary@ionlibrary[[1]])
specLibrary@ionlibrary[[1]]
## ----plotSpecLibraryIons, fig.retina=3----------------------------------------
plot(specLibrary@ionlibrary[[1]])
## ----plotSpecLibrary, fig.retina=3--------------------------------------------
plot(specLibrary)
## ----write.spectronaut, eval=TRUE---------------------------------------------
write.spectronaut(specLibrary, file = INPUT$OUTPUT_LIBRARY_FILE)
## ----save, eval=TRUE----------------------------------------------------------
save(specLibrary, file = INPUT$RDATA_LIBRARY_FILE)
## ----sessionInfo, echo=FALSE--------------------------------------------------
sessionInfo()
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