Registration and Call for Abstracts Open for Bioc2024

SGSeq

Splice event prediction and quantification from RNA-seq data


Bioconductor version: Release (3.18)

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 "4.3") 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")
SGSeq HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews AlternativeSplicing, ImmunoOncology, RNASeq, Software, Transcription
Version 1.36.0
In Bioconductor since BioC 3.0 (R-3.1) (9.5 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
System Requirements
URL
See More
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
Links To Me
Build Report Build Report

Package Archives

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

Source Package SGSeq_1.36.0.tar.gz
Windows Binary SGSeq_1.36.0.zip
macOS Binary (x86_64) SGSeq_1.36.0.tgz
macOS Binary (arm64) SGSeq_1.36.0.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