require(gcount) require(gcount) knitr::opts_chunk$set( comment = "#", error = FALSE, tidy = FALSE, cache = FALSE, collapse=TRUE) # options(datatable.auto.index=FALSE)
We've developed three packages for performing differential analysis of NGS
data, namely gread, gcount and ganalyse. In short,
gread enables loading or reading in the required data quickly from many different formats in which NGS data and gene annotations are available.
gcount counts the reads depending on user configuration on raw counts.
ganalyse then allows to perform differential gene expression analysis
using many methods such as limma, voomlimma (for FPKM), edger on the
read counts.
In this vignette, we'll discuss the gcount package.
gcount is an R-package that allows to obtain read counts quickly and easily
from RNASeq data to be used in downstream analyses.
gcount takes a bam/bed file as input.
allows specification of paired or single end data.
allows specification of unstranded, first-strand or second-strand
specific.
filter reads based on number of mismatches prior to counting.
consider or ignore reads that map to overlapping genes.
and allows to count reads that overlap features genes, exons or introns.
We can obtain counts by using get_counts function.
counts = get_counts("sample.bam", "sample.gtf", feature="gene_exon", type="union", library="unstranded", paired=FALSE, multiple_feature_overlaps=FALSE, verbose=FALSE) head(counts[order(-reads)])
We count the number of reads for all the genes present in "sample.gtf".
feature="gene_exon" counts reads within each gene across exons alone.
type tells how to handle multiple identical or overlapping features.
"union" is the most common model (default).
The reads in "sample.bam" file is single-end unstranded. Hence
library="unstranded" and paired=FALSE.
multiple_feature_overlaps is to decide if reads overlapping multiple
genes should be counted or not. Default is to skip those reads.
See ?get_counts for a more complete description.
bam and annotation objects:get_counts() also accepts objects as inputs (in addition to file names).
Let's say you have already loaded "sample.gtf" on to a variable called
"gtf". Then we can simply do:
gtf = gread::read_format("sample.gtf") counts = get_counts("sample.bam", gtf, feature="gene_exon", type="union", library="unstranded", paired=FALSE, multiple_feature_overlaps=FALSE, verbose=FALSE) head(counts[order(-reads)])
We can also provide bed files (or objects) as input to reads argument of
get_counts().
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