Description Usage Arguments Value Examples
View source: R/HTSanalyzeR4MAGeCK.R
This function writes a shiny report following a complete analyses of CRISPR data preprocessed by MAGeCK based on the two classes GSCA (Gene Set Collection Analysis) and NWA (NetWork Analysis) of this package.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | HTSanalyzeR4MAGeCK(
MAGeCKdata,
selectDirection = "negative",
doGSOA = FALSE,
doGSEA = TRUE,
hitsCutoffLogFC = NULL,
hitsCutoffPval = NULL,
listOfGeneSetCollections,
species = "Hs",
initialIDs = "SYMBOL",
keepMultipleMappings = TRUE,
duplicateRemoverMethod = "max",
orderAbsValue = FALSE,
pValueCutoff = 0.05,
pAdjustMethod = "BH",
nPermutations = 1000,
minGeneSetSize = 15,
exponent = 1,
verbose = TRUE,
GSEA.by = "HTSanalyzeR2",
keggGSCs = NULL,
goGSCs = NULL,
msigdbGSCs = NULL,
doNWA = FALSE,
interactionMatrix = NULL,
reportDir = "HTSanalyzerReport",
nwAnalysisGenetic = FALSE,
nwAnalysisFdr = 0.001
)
|
MAGeCKdata |
A result file for CRISPR data preprocessed by MAGeCK. |
selectDirection |
A character specifying which direction to choose from MAGeCK result, should either be 'positive' or 'negative'. |
doGSOA |
A logic value specifying whether to do hypergeometric test or not, default is FALSE. |
doGSEA |
A logic value specifying whether to do gene set enrichment analysis or not, default is TRUE. |
hitsCutoffLogFC |
A numeric value as cutoff to choose hits based on log2fold change when doing GSOA. Genes with absolute log2fold change greater than this cutoff would be choosen as hits. Either 'hitsCutoffLogFC' or 'hitsCutoffPval' is needed when doing GSOA. |
hitsCutoffPval |
A numeric value as cutoff to choose hits based on pvalue when doing GSOA. Genes with pvalues less than this cutoff would be choosen as hits. Either 'hitsCutoffLogFC' or 'hitsCutoffPval' is needed when doing GSOA. |
listOfGeneSetCollections |
A list of gene set collections (a 'gene set collection' is a list of gene sets). |
species |
A single character value specifying the species for which the data should be read. |
initialIDs |
A single character value specifying the type of initial identifiers for input geneList |
keepMultipleMappings |
A single logical value. If TRUE, the function keeps the entries with multiple mappings (first mapping is kept). If FALSE, the entries with multiple mappings will be discarded. |
duplicateRemoverMethod |
A single character value specifying the method to remove the duplicates. See duplicateRemover for details. |
orderAbsValue |
A single logical value indicating whether the values should be converted to absolute values and then ordered (if TRUE), or ordered as they are (if FALSE). |
pValueCutoff |
A single numeric value specifying the cutoff for p-values considered significant in gene set collection analysis. |
pAdjustMethod |
A single character value specifying the p-value adjustment method to be used (see 'p.adjust' for details) in gene set collection analysis. |
nPermutations |
A single integer or numeric value specifying the number of permutations for deriving p-values in GSEA. |
minGeneSetSize |
A single integer or numeric value specifying the minimum number of elements shared by a gene set and the input total genes. Gene sets with fewer than this number are removed from both hypergeometric analysis and GSEA. |
exponent |
A single integer or numeric value used in weighting phenotypes in GSEA. |
verbose |
A single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE) |
GSEA.by |
A single character value to choose which algorithm to do GSEA. Valid value
could either be "HTSanalyzeR2"(default) or "fgsea". If performed by "fgsea", the result explanation
please refer to |
keggGSCs |
A character vector of names of all KEGG gene set collections. |
goGSCs |
A character vector of names of all GO gene set collections. |
msigdbGSCs |
A character vector of names of all MSigDB gene set collections. |
doNWA |
A logic value specifying whether to do subnetwork analysis or not, default is FALSE. |
interactionMatrix |
An interaction matrix including columns 'InteractionType', 'InteractorA' and 'InteractorB'. If this matrix is available, the interactome can be directly built based on it. |
reportDir |
A single character value specifying the directory to store reports. For default the enrichment analysis reports will be stored in the directory called "HTSanalyzerReport". |
nwAnalysisGenetic |
A single logical value. If TRUE, genetic interactions will be kept; otherwise, they will be removed from the data set. |
nwAnalysisFdr |
A single numeric value specifying the false discovery for the scoring of nodes (see BioNet::scoreNodes and Dittrich et al., 2008 for details) |
This pipeline function will finally generate a shiny report including all the results in. All the results would be stored as RData named 'results.RData' under a new automatic generated directory. It can be loaded into R by 'readRDS(results.RData)'.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ## Not run:
data(d7)
library(GO.db)
library(org.Hs.eg.db)
library(KEGGREST)
## set up a list of gene set collections
GO_MF <- GOGeneSets(species="Hs", ontologies=c("MF"))
PW_KEGG <- KeggGeneSets(species="Hs")
ListGSC <- list(GO_MF=GO_MF, PW_KEGG=PW_KEGG)
## start analysis
HTSanalyzeR4MAGeCK(MAGeCKdata = d7,
selectDirection = "negative",
doGSOA = TRUE,
doGSEA = TRUE,
hitsCutoffPval = 0.01,
listOfGeneSetCollections = ListGSC,
species = "Hs",
initialIDs = "SYMBOL",
pValueCutoff = 0.05,
nPermutations = 1000,
minGeneSetSize = 200,
keggGSCs=c("PW_KEGG"),
goGSCs = c("GO_MF"),
doNWA = TRUE,
nwAnalysisFdr = 0.0001)
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.