To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SGSeq")
In most cases, you don't need to download the package archive at all.
SGSeq
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Splice event prediction and quantification from RNA-seq data
Bioconductor version: Release (3.5)
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
Maintainer: Leonard Goldstein <goldstel at gene.com>
Citation (from within R,
enter citation("SGSeq")):
Installation
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SGSeq")
Documentation
| HTML | R Script | SGSeq |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | AlternativeSplicing, RNASeq, Software, Transcription |
| Version | 1.10.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) (3 years) |
| License | Artistic-2.0 |
| Depends | IRanges, GenomicRanges(>= 1.23.21), Rsamtools, SummarizedExperiment, methods |
| Imports | AnnotationDbi, BiocGenerics, Biostrings, GenomicAlignments, GenomicFeatures, GenomeInfoDb, RUnit, S4Vectors(>= 0.9.39), grDevices, graphics, igraph, parallel, rtracklayer, stats |
| LinkingTo | |
| Suggests | BiocStyle, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, knitr, rmarkdown |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | EventPointer |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | SGSeq_1.10.0.tar.gz |
| Windows Binary | SGSeq_1.10.0.zip |
| Mac OS X 10.11 (El Capitan) | SGSeq_1.10.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/SGSeq |
| Package Short Url | http://bioconductor.org/packages/SGSeq/ |
| Package Downloads Report | Download Stats |
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