htseq_count: htseq_count

In omicsCore/SEQprocess: SEQprocess : a modularized and customizable pipeline framework for NGS processing in R package.

Description

A wrapper function to run htseq-count for mRNA or miRNA quantitation

Usage

htseq_count(RNAtype="mRNA", fns.bam, sample.name, output.dir, Mode="intersection-nonempty", stranded="no", idattr="gene_id", htseq.r="pos", htseq.a=10, ref.gtf, mir.gff, run.cmd=TRUE, mc.cores=1)

Arguments

fns.bam	Path to input BAM or SAM files
sample.name	A character vector for the sample names
output.dir	Output directory
stranded	A parameter value for -s in htseq-count. Whether the data is from a strand-specific assay (default:no)
idattr	A parameter value for -i in htseq-count. GFF attribute to be used as feature ID (default:"gene_id")
htseq.r	A parameter value for -r in htseq-count. Sorting order method (default:"pos")
htseq.a	A parameter value for -a in htseq-count. Skip all reads with alignment quality lower than the given minimum value (default: 10)
ref.gtf	Directoy stored at reference gtf file
mir.gff	Directoy stored at micro-RNA reference gff file
run.cmd	Whether to execute the command line (default=TRUE)
mc.cores	The number of cores to use. Must be at least one(default=1), and parallelization requires at least two cores.
MODE	A parameter value for -m in htseq-count. Mode to handle reads overlapping more than one feature (default:intersection-nonempty)

Details

Counting reads in features. Given a file with aligned sequencing reads and a list of genomic features, a common task is to count how many reads map to each feature.

Value

Text file included read count information

References

HTSeq—a Python framework to work with high-throughput sequencing data

See Also

{https://htseq.readthedocs.io/en/release_0.9.1/

omicsCore/SEQprocess documentation built on May 7, 2020, 4:18 a.m.