peak_calling <- function(IP_BAM,
INPUT_BAM,
GENE_ANNO_GTF,
paired_end = FALSE,
Genome = "hg19",
output_dir){
##MeRIP-seq data alignment
MeRIP_Seq_Alignment <- scanMeripBAM(
bam_ip = IP_BAM,
bam_input = INPUT_BAM,
paired_end = FALSE)
##Perform peak calling on exons
###If either genome or bsgenome arguments are provided, the GC content bias correction will be performed while peak calling.
SummarizedExomePeaks <- exomePeakCalling(merip_bams = MeRIP_Seq_Alignment,
gff_dir = GENE_ANNO_GTF,
genome = Genome)
##Estimate correction factors
###the normalization methods used will be controlled by the functions estimateSeqDepth() and normalizeGC().
####User can combine multiple normalization approaches, such as adding the conditional quantile normalization introduced in
SummarizedExomePeaks <- estimateSeqDepth(SummarizedExomePeaks)
SummarizedExomePeaks <- normalizeGC(SummarizedExomePeaks)
size_factor <- SummarizedExomePeaks$sizeFactor
## Report the GLM statistics
SummarizedExomePeaks <- glmM(SummarizedExomePeaks)
## Export peak calling result
exportResults(SummarizedExomePeaks,
save_dir = output_dir)
save(size_factor,file=paste0(output_dir,"/","size_factor.Rdata"))
}
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