SGSeq

DOI: 10.18129/B9.bioc.SGSeq  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see SGSeq.

Splice event prediction and quantification from RNA-seq data

Bioconductor version: 3.17

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 [cre, aut]

Maintainer: Leonard Goldstein <ldgoldstein at gmail.com>

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SGSeq")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("SGSeq")

 

HTML	R Script	SGSeq
PDF		Reference Manual
Text		NEWS

Details

biocViews	AlternativeSplicing, ImmunoOncology, RNASeq, Software, Transcription
Version	1.34.0
In Bioconductor since	BioC 3.0 (R-3.1) (9 years)
License	Artistic-2.0
Depends	R (>= 4.0), IRanges(>= 2.13.15), GenomicRanges(>= 1.31.10), Rsamtools(>= 1.31.2), SummarizedExperiment, methods
Imports	AnnotationDbi, BiocGenerics(>= 0.31.5), Biostrings(>= 2.47.6), GenomicAlignments(>= 1.15.7), GenomicFeatures(>= 1.31.5), GenomeInfoDb, RUnit, S4Vectors(>= 0.23.19), grDevices, graphics, igraph, parallel, rtracklayer(>= 1.39.7), stats
LinkingTo
Suggests	BiocStyle, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, knitr, rmarkdown
SystemRequirements
Enhances
URL
Depends On Me	EventPointer
Imports Me	Rhisat2
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	SGSeq_1.34.0.tar.gz
Windows Binary	SGSeq_1.34.0.zip
macOS Binary (x86_64)	SGSeq_1.34.0.tgz
macOS Binary (arm64)	SGSeq_1.34.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/SGSeq
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/SGSeq
Bioc Package Browser	https://code.bioconductor.org/browse/SGSeq/
Package Short Url	https://bioconductor.org/packages/SGSeq/
Package Downloads Report	Download Stats