This repository contains the development version of the R package regsplice
.
The release version is available from Bioconductor.
The regsplice
package implements statistical methods for the detection of differential exon usage (differential splicing) in RNA sequencing (RNA-seq) and exon microarray data sets. The regsplice
methods are based on the use of the lasso (L1-regularization) to improve the power of standard generalized linear models. A key advantage is that runtimes are fast compared to other leading approaches.
A paper describing the statistical methodology and performance comparisons with other methods is currently in preparation.
The release version can be installed from Bioconductor using the Bioconductor installer. This will also install all required dependencies. This is the recommended option for most users.
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("regsplice")
The development version can be installed from this GitHub repository using devtools::install_github
.
install.packages("devtools")
library(devtools)
install_github("lmweber/regsplice")
Alternatively, the development version can also be installed using the "Devel" version of Bioconductor (see Bioconductor documentation for details). However, the Bioconductor Devel version may sometimes be a few days behind the GitHub version.
The regsplice
package depends on:
glmnet
, pbapply
(from CRAN)
limma
, edgeR
, SummarizedExperiment
(from Bioconductor)
If you install using the Bioconductor installer, all dependencies will be installed automatically.
If you install from GitHub, the Bioconductor dependencies need to be installed separately.
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install(c("limma", "edgeR", "SummarizedExperiment"))
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