get_mapp | R Documentation |
Compute mappability for each bin. Note that scDNA sequencing is whole-genome amplification and the mappability score is essential to determine variable binning method. Mappability track for 100-mers on the GRCh37/hg19 human reference genome from ENCODE is pre-saved. Compute the mean of mappability scores that overlapped reads map to bins, weighted by the width of mappability tracks on the genome reference. Use liftOver utility to calculate mappability for hg38, which is pre-saved as well. For mm10, there are two workarounds: 1) set all mappability to 1 to avoid extensive computation; 2) adopt QC procedures based on annotation results, e.g., filter out bins within black list regions, which generally have low mappability.
get_mapp(ref, hgref = "hg19")
ref |
GRanges object returned from |
hgref |
reference genome. This should be 'hg19', 'hg38' or 'mm10'.
Default is human genome |
mapp |
Vector of mappability for each bin/target |
Rujin Wang rujin@email.unc.edu
## Not run: library(WGSmapp) library(BSgenome.Hsapiens.UCSC.hg38) bamfolder <- system.file('extdata', package = 'WGSmapp') bamFile <- list.files(bamfolder, pattern = '*.dedup.bam$') bamdir <- file.path(bamfolder, bamFile) sampname_raw <- sapply(strsplit(bamFile, '.', fixed = TRUE), '[', 1) bambedObj <- get_bam_bed(bamdir = bamdir, sampname = sampname_raw, hgref = "hg38") bamdir <- bambedObj$bamdir sampname_raw <- bambedObj$sampname ref_raw <- bambedObj$ref mapp <- get_mapp(ref_raw, hgref = "hg38") ## End(Not run)
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