SGSeq
Splice event prediction and quantification from RNA-seq data
Bioconductor version: 3.24 · Package version: 1.47.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SGSeq")Details
| Maintainer | Leonard Goldstein <ldgoldstein@gmail.com> |
| Author | Leonard Goldstein [cre, aut] |
| License | Artistic-2.0 |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | AlternativeSplicing, ImmunoOncology, RNASeq, Software, Transcription |
| Package Short Url | https://bioconductor.org/packages/SGSeq/ |
Citation
From within R, enter citation("SGSeq"):
Leonard Goldstein. SGSeq: Splice event prediction and quantification from RNA-seq data. doi:10.18129/B9.bioc.SGSeq, R package version 1.47.0, https://bioconductor.org/packages/SGSeq.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | SGSeq_1.47.0.tar.gz |
| Windows binary (x86_64) | SGSeq_1.47.0.zip |
| macOS binary (arm64) | SGSeq_1.47.0.tgz |
| macOS binary (x86_64) | SGSeq_1.47.0.tgz |
Dependencies
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), Seqinfo, grDevices, graphics, igraph, parallel, rtracklayer (>= 1.39.7), stats
Suggests: BiocStyle, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, knitr, rmarkdown
Reverse dependencies
Depends On Me (1): EventPointer
Imports Me (1): Rhisat2
Suggests Me (1): FRASER