TCGA.pipe {ELMER} | R Documentation |
ELMER analysis pipeline for TCGA data. This pipeline combine every steps of ELMER analyses: get.feature.probe, get.diff.meth, get.pair, get.permu, get.enriched.motif and get.TFs. Every steps' results are saved.
TCGA.pipe(disease, genome = "hg38", analysis = "all", wd = getwd(), cores = 1, mode = "unsupervised", Data = NULL, diff.dir = "hypo", genes = NULL, mutant_variant_classification = c("Frame_Shift_Del", "Frame_Shift_Ins", "Missense_Mutation", "Nonsense_Mutation", "Splice_Site", "In_Frame_Del", "In_Frame_Ins", "Translation_Start_Site", "Nonstop_Mutation"), group.col = "TN", group1 = "Tumor", group2 = "Normal", ...)
disease |
TCGA short form disease name such as COAD |
genome |
Data aligned against which genome of reference. Options: "hg19", "hg38" (default) |
analysis |
A vector of characters listing the analysis need to be done. Analysis can be "download","distal.probes","diffMeth","pair","motif","TF.search". Default is "all" meaning all the analysis will be processed. |
wd |
A path shows working dirctory. Default is "./" |
cores |
A interger which defines number of core to be used in parallel process. Default is 1: don't use parallel process. |
mode |
This option will automatically set the percentage of samples to be used in the analysis. Options: "supervised" (use 100% of samples) or "unsupervised" (use 20% of samples). |
Data |
A path shows the folder containing DNA methylation, expression and clinic data |
diff.dir |
A character can be "hypo" or "hyper", showing dirction DNA methylation changes. If it is "hypo", get.diff.meth function will identify all significantly hypomethylated CpG sites; If "hyper", get.diff.meth function will identify all significantly hypermethylated CpG sites |
genes |
List of genes for which mutations will be verified. A column in the MAE with the name of the gene will be created with two groups WT (tumor samples without mutation), MUT (tumor samples w/ mutation), NA (not tumor samples) |
mutant_variant_classification |
List of TCGA variant classification from MAF files to consider a samples mutant. Only used when argument gene is set. |
group.col |
A column defining the groups of the sample. You can view the available columns using: colnames(MultiAssayExperiment::colData(data)). |
group1 |
A group from group.col. ELMER will run group1 vs group2. That means, if direction is hyper, get probes hypermethylated in group 1 compared to group 2. |
group2 |
A group from group.col. ELMER will run group1 vs group2. That means, if direction is hyper, get probes hypermethylated in group 1 compared to group 2. |
... |
A list of parameters for functions: GetNearGenes, get.feature.probe, get.diff.meth, get.pair |
Different analysis results.
## Not run: distal.probe <- TCGA.pipe(disease = "LUSC", analysis="distal.enhancer", wd="~/") TCGA.pipe(disease = "LUSC",analysis = "all", genome = "hg19", cores = 1, permu.size=300, Pe=0.01) projects <- TCGAbiolinks:::getGDCprojects()$project_id projects <- gsub("TCGA-","",projects[grepl('^TCGA',projects,perl=TRUE)]) for(proj in projects) TCGA.pipe(disease = proj,analysis = "download") plyr::alply(sort(projects),1,function(proj) { tryCatch({ print(proj); TCGA.pipe(disease = proj,analysis = c("createMAE"))}) }, .progress = "text") plyr::alply(sort(projects),1,function(proj) { tryCatch({ print(proj); TCGA.pipe(disease = proj, analysis = c("diffMeth","pair", "motif","TF.search"))}) }, .progress = "text") # Evaluation mutation TCGA.pipe(disease = "LUSC",analysis = "createMAE",gene = "NFE2L2") TCGA.pipe(disease = "LUSC",analysis = c("diffMeth","pair", "motif","TF.search"), mode = "supervised", group.col = "NFE2L2", group1 = "Mutant", group2 = "WT", diff.dir = c("hypo"), dir.out = "LUSC_NFE2L2_MutvsWT") ## End(Not run)