To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SGSeq")

In most cases, you don't need to download the package archive at all.

SGSeq

DOI: 10.18129/B9.bioc.SGSeq    

This is the development version of SGSeq; for the stable release version, see SGSeq.

Splice event prediction and quantification from RNA-seq data

Bioconductor version: Development (3.6)

SGSeq is a software package for analyzing splice events from RNA-seq data. Input data are RNA-seq reads mapped to a reference genome in BAM format. Genes are represented as a splice graph, which can be obtained from existing annotation or predicted from the mapped sequence reads. Splice events are identified from the graph and are quantified locally using structurally compatible reads at the start or end of each splice variant. The software includes functions for splice event prediction, quantification, visualization and interpretation.

Author: Leonard Goldstein

Maintainer: Leonard Goldstein <goldstel at gene.com>

Citation (from within R, enter citation("SGSeq")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SGSeq")

Documentation

HTML R Script SGSeq
PDF   Reference Manual
Text   NEWS

Details

biocViews AlternativeSplicing, RNASeq, Software, Transcription
Version 1.11.2
In Bioconductor since BioC 3.0 (R-3.1) (3 years)
License Artistic-2.0
Depends IRanges, GenomicRanges(>= 1.23.21), Rsamtools, SummarizedExperiment, methods
Imports AnnotationDbi, BiocGenerics, Biostrings, GenomicAlignments, GenomicFeatures, GenomeInfoDb, RUnit, S4Vectors(>= 0.9.39), grDevices, graphics, igraph, parallel, rtracklayer(>= 1.37.2), stats
LinkingTo
Suggests BiocStyle, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, knitr, rmarkdown
SystemRequirements
Enhances
URL
Depends On Me EventPointer
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package SGSeq_1.11.2.tar.gz
Windows Binary SGSeq_1.11.2.zip
Mac OS X 10.11 (El Capitan) SGSeq_1.11.2.tgz
Source Repository git clone https://git.bioconductor.org/packages/SGSeq
Package Short Url http://bioconductor.org/packages/SGSeq/
Package Downloads Report Download Stats

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