SGSeq

Splice event prediction and quantification from RNA-seq data

Bioconductor version: Release (3.20)

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 "4.4") 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")

SGSeq	HTML	R Script
Reference Manual	PDF
NEWS	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	AlternativeSplicing, ImmunoOncology, RNASeq, Software, Transcription
Version	1.40.0
In Bioconductor since	BioC 3.0 (R-3.1) (10 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
System Requirements
URL

Suggests	BiocStyle, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, knitr, rmarkdown
Linking To
Enhances
Depends On Me	EventPointer
Imports Me	Rhisat2
Suggests Me	FRASER
Links To Me
Build Report	Build Report

Package Archives

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

Source Package	SGSeq_1.40.0.tar.gz
Windows Binary (x86_64)	SGSeq_1.40.0.zip
macOS Binary (x86_64)	SGSeq_1.40.0.tgz
macOS Binary (arm64)	SGSeq_1.40.0.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