Learn R Programming

easyRNASeq (version 2.8.2)

easyRNASeq package: Count summarization and normalization pipeline for Next Generation Sequencing data.

Description

Offers functionalities to summarize read counts per feature of interest, e.g. exons, transcripts, genes, etc. Offers functionalities to normalize the summarized counts using 3rd party packages like DESeq or edgeR.

Arguments

Methods

The main function easyRNASeq will summarize the counts per feature of interest, for as many samples as provided and will return a count matrix (N*M) where N are the features and M the samples. This data can be corrected to RPKM in which case a matrix of corrected value is returned instead, with the same dimensions. Alternatively a RangedSummarizedExperiment can be returned and this is expected to be the default in the upcoming version of easyRNASeq (as of 1.5.x). If the necessary sample information are provided, the data can be normalized using either DESeq or edgeR and the corresponding package object returned. For more insider details, and step by step functions, see: ll{ ShortRead methods for pre-processing the data. easyRNASeq annotation methods for getting the annotation. easyRNASeq coverage methods for computing the coverage from a Short Read Alignment file. easyRNASeq summarization methods for summarizing the data. easyRNASeq correction methods for correcting the data (i.e. generating RPKM). edgeR methods for post-processing the data. DESeq methods for post-processing the data. }

Details

ll{ Package: easyRNASeq Type: Package Version: 2.7.2 Date: 2015-12-18 License: Artistic-2.0 LazyLoad: yes Depends: methods, parallel, Biobase, BiocGenerics, biomaRt, Biostrings, edgeR, DESeq, genomeIntervals, GenomeInfoDb, GenomicAlignments, GenomicRanges, SummarizedExperiment, graphics, IRanges, LSD, Rsamtools, S4Vectors, ShortRead, utils Suggests: BSgenome.Dmelanogaster.UCSC.dm3 }

See Also

The class RNAseq specification: RNAseq

The default output class specification: RangedSummarizedExperiment

The imported packages: biomaRt BiocParallel edgeR genomeIntervals Biostrings BSgenome DESeq GenomicRanges IRanges Rsamtools ShortRead

The suggested packages: parallel GenomicFeatures

The following classes and functions that are made available from other packages:

  • Classes
{ BamFileList CountDataSet RangedData RangedSummarizedExperiment } Functions/Methods{ DESeq estimate size factor and estimate dispersion functions The RangedSummarizedExperiment assay accessor The locfit function The BamFileList constructor The IRanges constructor The RangedData constructor For the SRFilterResult, chromosomeFilter, compose and nFilter methods }

Examples

Run this code
library("RnaSeqTutorial")
	library(BSgenome.Dmelanogaster.UCSC.dm3)

	## creating a count table from 4 bam files
	count.table <- easyRNASeq(filesDirectory=
		    			system.file(
					"extdata",
					package="RnaSeqTutorial"),
					pattern="[A,C,T,G]{6}\\.bam$",
				format="bam",
				readLength=36L,
				organism="Dmelanogaster",
				chr.sizes=as.list(seqlengths(Dmelanogaster)),
				annotationMethod="rda",
				annotationFile=system.file(
				                            "data",
							    "gAnnot.rda",
							    package="RnaSeqTutorial"),
				count="exons")

Run the code above in your browser using DataLab