Description Usage Arguments Value Author(s) Examples
View source: R/tileCount2.R View source: R/tileCount2.R
Perform overlap queries between reads and genome by sliding windows Count reads over sliding windows.
1 2 3 | tileCount2(reads, fragment.length = 100, windowSize = 50000,
restrict = paste0("chr", c(1:19, "X", "Y")), step = 1000,
filter = 0, pe = "both")
|
reads |
An object that represents the names and path of the bam files to be counted. If reads are more than 1 bam files, it should be a vector of character with full path. This function now works for paired end reads |
fragment.length |
integer(1). An integer scalar or a list of two integer scalars/vectors, containing the average length(s) of the sequenced fragments in each libary. |
windowSize |
numeric(1) or integer(1). Size of the windows. |
restrict |
restrict to a set of chromosomes, default to mouse chromosomes. |
step |
numeric(1) or integer(1). Step of generating silding windows. |
filter |
default to 0 without filtering. An integer scalar for the minimum count sum across libraries for each window |
pe |
a character string indicating whether paired-end data is present; set to "none", "both", "first" or "second" |
A RangedSummarizedExperiment object with chromosome-level depth 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
Jun Yu,Herv<c3><a9> Pag<c3><a8>s and Julie Zhu
1 2 3 4 5 6 7 8 9 | if (interactive())
{
fls <- list.files(system.file("extdata", package="NADfinder"),
recursive=FALSE, pattern="*bam$", full=TRUE)
names(fls) <- basename(fls)
se <- tileCount2(reads = fls,
windowSize=50000, step=10000)
}
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