peakGeneCor {FindIT2} | R Documentation |
peakGeneCor
peakGeneCor(mmAnno, peakScoreMt, geneScoreMt, parallel = FALSE, verbose = TRUE)
mmAnno |
the annotated GRange object from mm_geneScan or mm_nearestGene |
peakScoreMt |
peak count matrix. The rownames are feature_id in mmAnno, while the colnames are sample names. |
geneScoreMt |
gene count matirx. The rownames are gene_id in mmAnno, while the colnames are sample names. |
parallel |
whehter you want to using bplapply to speed up calculation |
verbose |
whether you want to report detailed running message |
mmAnno with Cor, pvalue,padj,qvalue column
if (require(TxDb.Athaliana.BioMart.plantsmart28)){ Txdb <- TxDb.Athaliana.BioMart.plantsmart28 seqlevels(Txdb) <- paste0("Chr", c(1:5, "M", "C")) data("RNA_normCount") data("ATAC_normCount") peak_path <- system.file("extdata", "ATAC.bed.gz", package = "FindIT2") peak_GR <- loadPeakFile(peak_path)[1:100] mmAnno <- mm_geneScan(peak_GR, Txdb) ATAC_colData <- data.frame( row.names = colnames(ATAC_normCount), type = gsub("_R[0-9]", "", colnames(ATAC_normCount)) ) ATAC_normCount_merge <- integrate_replicates(ATAC_normCount, ATAC_colData) RNA_colData <- data.frame( row.names = colnames(RNA_normCount), type = gsub("_R[0-9]", "", colnames(RNA_normCount)) ) RNA_normCount_merge <- integrate_replicates(RNA_normCount, RNA_colData) mmAnnoCor <- peakGeneCor( mmAnno = mmAnno, peakScoreMt = ATAC_normCount_merge, geneScoreMt = RNA_normCount_merge, parallel = FALSE ) mmAnnoCor }