tileCount {NADfinder} | R Documentation |
tileCount extends summarizeOverlaps by finding coverage for each fixed window in the whole genome
tileCount(reads, genome, excludeChrs = c("chrM", "M", "Mt", "MT"), windowSize = 50000, step = 10000, mode = IntersectionNotStrict, dataOverSamples = FALSE, ...)
reads |
A GRanges,
GRangesList (should be one read per list element),
GAlignments,
GAlignmentsList,
GAlignmentPairs or
BamFileList object that represents the data to be
counted by |
genome |
A BSgenome object from/on which to get/set the sequence and metadata information. |
excludeChrs |
A vector of string: chromosomes/scaffolds of no interest for NAD analysis. see summarizeOverlaps. default is countByOverlaps, alia of countOverlaps(features, reads, ignore.strand=ignore.strand) |
windowSize |
numeric(1) or integer(1). Size of the windows. |
step |
numeric(1) or integer(1). Step of generating silding windows. |
mode |
One of the pre-defined count methods. |
dataOverSamples |
logical(1). Data over several samples when use GRangesList as input. |
... |
Additional arguments passed to
|
A RangedSummarizedExperiment object. The assays slot holds the counts, rowRanges holds the annotation from the sliding widows of genome. metadata contains lib.size.chrom for holding chromosome-level sequence depth
Jianhong Ou, Haibo Liu, Herve Pages and Julie Zhu
if (interactive()) { fls <- list.files(system.file("extdata", package="NADfinder"), recursive=FALSE, pattern="*bam$", full=TRUE) names(fls) <- basename(fls) if (!require(BSgenome.Mmusculus.UCSC.mm10)) { source("https://bioconductor.org/biocLite.R") biocLite("BSgenome.Mmusculus.UCSC.mm10") library(BSgenome.Mmusculus.UCSC.mm10) } se <- tileCount(reads = fls, genome = Mmusculus, excludeChrs = c("chrM", paste0("chr", c(1:17,19)), "chrX", "chrY"), windowSize=50000, step=10000) }