scan_spike_contigs: pretty much what it says: scan spike contigs from a BAM or...

In trichelab/spiky: Spike-in calibration for cell-free MeDIP

pretty much what it says: scan spike contigs from a BAM or CRAM file

Description

default workflow is

Usage

scan_spike_contigs(bam, spike, how = "max", param = NULL, mc.cores = 16, ...)

Arguments

bam	the BAM or CRAM filename, or a vector of such filenames
spike	the spike-in reference database (e.g. data(spike))
how	how to summarize the per-spike coverage (max)
param	a ScanBamParam object, or NULL (will default to MAPQ=20 etc)
mc.cores	Number of cores to run on (default 16)
...	additional arguments to pass to scanBamFlag()

Details

1. scan spike contigs and count fragments per contig or per bin.

2. fit the appropriate model for adjusting genomic contigs based on spikes.

3. scan and adjust binned fragment tallies along genomic contigs per above.

scan_spike_contigs implements step 1.

If multiple BAM or CRAM filenames are provided, all indices will be checked before attempting to run through any of the files.

Value

     a CompressedGRangesList with bin- and spike-level coverage

See Also

    Rsamtools::ScanBamParam

Examples

library(GenomicRanges)
data(spike, package="spiky")
sb <- system.file("extdata", "example.spike.bam", package="spiky",
                  mustWork=TRUE) # switch to a CRAM
res <- scan_spike_contigs(sb, spike=spike) # use default ScanBamParam
summary(res)

trichelab/spiky documentation built on Sept. 17, 2022, 8:44 a.m.