SGSeq

DOI: 10.18129/B9.bioc.SGSeq  

Splice event prediction and quantification from RNA-seq data

Bioconductor version: Release (3.16)

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>

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

Installation

To install this package, start R (version "4.2") 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 1.32.0
In Bioconductor since BioC 3.0 (R-3.1) (8.5 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_1.32.0.tar.gz
Windows Binary SGSeq_1.32.0.zip
macOS Binary (x86_64) SGSeq_1.32.0.tgz
macOS Binary (arm64) SGSeq_1.32.0.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

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: