\name{easyRNASeq-package}
\alias{easyRNASeq-package}

\docType{package}

\title{
	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 \code{\link[DESeq:newCountDataSet]{DESeq}} or \code{\link[edgeR:DGEList]{edgeR}}.
}
\details{
\tabular{ll}{
Package: \tab easyRNASeq\cr
Type: \tab Package\cr
Version: \tab 1.1.10\cr
Date: \tab 2012-03-06\cr
License: \tab Artistic-2.0\cr
LazyLoad: \tab yes\cr
Depends: \tab methods, parallel, biomaRt, edgeR, DESeq, genomeIntervals, Rsamtools, ShortRead, RnaSeqTutorial\cr
Suggests: \tab BSgenome.Dmelanogaster.UCSC.dm3
}

The main function \code{\link[easyRNASeq:easyRNASeq]{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 will be the features and M the samples. This data can be corrected to \pkg{RPKM} in which case a matrix of corrected value is returned instead, with the same dimensions. If the necessary sample information are provided, the data can be normalized using either \code{\link[DESeq:newCountDataSet]{DESeq}} or \code{\link[edgeR:DGEList]{edgeR}} and the corresponding package object returned.

For more insider details, and step by step functions, see:
\tabular{ll}{
	\code{\link[easyRNASeq:ShortRead-methods]{ShortRead methods}} for pre-processing the data.
	\code{\link[easyRNASeq:easyRNASeq-annotation-methods]{easyRNASeq annotation methods}} for getting the annotation.
	\code{\link[easyRNASeq:easyRNASeq-coverage-methods]{easyRNASeq coverage methods}} for computing the coverage from a Short Read Alignment file.
	\code{\link[easyRNASeq:easyRNASeq-summarization-methods]{easyRNASeq summarization methods}} for summarizing the data.
	\code{\link[easyRNASeq:easyRNASeq-correction-methods]{easyRNASeq correction methods}} for correcting the data (i.e. generating RPKM).
	\code{\link[easyRNASeq:edgeR-methods]{edgeR methods}} for post-processing the data.
	\code{\link[easyRNASeq:DESeq-methods]{DESeq methods}} for post-processing the data.
	}
}
\author{
	Nicolas Delhomme
	Maintainer: Nicolas Delhomme <delhomme@embl.de>
}

\keyword{ package }

\seealso{
	The class RNAseq specification:
	\code{\linkS4class{RNAseq}}

	The imported packages:
	\code{\link[biomaRt:useMart]{biomaRt}}
	\code{\link[edgeR:DGEList]{edgeR}}
	\code{\link[genomeIntervals:Genome_intervals_stranded-class]{genomeIntervals}}
	\code{\link[Biostrings:XString-class]{Biostrings}}
	\code{\link[BSgenome:BSgenome-class]{BSgenome}}
	\code{\link[DESeq:newCountDataSet]{DESeq}}
	\code{\link[GenomicRanges:GRanges-class]{GenomicRanges}}	
	\code{\link[IRanges:IRanges-constructor]{IRanges}}
	\code{\link[Rsamtools:scanBam]{Rsamtools}}
	\code{\link[ShortRead:readAligned]{ShortRead}}

	The suggested packages:
	\code{\link[parallel:makeCluster]{parallel}}
	\code{\link[GenomicFeatures:TranscriptDb-class]{GenomicFeatures}}
}

\examples{
	\dontrun{
	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")

	}
}