saseR
Scalable Aberrant Splicing and Expression Retrieval
Bioconductor version: 3.23 · Package version: 1.8.0
saseR is a highly performant and fast framework for aberrant expression and splicing analyses. The main functions are: \itemize{ \item \code{\link{BamtoAspliCounts}} - Process BAM files to ASpli counts \item \code{\link{convertASpli}} - Get gene, bin or junction counts from ASpli SummarizedExperiment \item \code{\link{calculateOffsets}} - Create an offsets assays for aberrant expression or splicing analysis \item \code{\link{saseRfindEncodingDim}} - Estimate the optimal number of latent factors to include when estimating the mean expression \item \code{\link{saseRfit}} - Parameter estimation of the negative binomial distribution and compute p-values for aberrant expression and splicing } For information upon how to use these functions, check out our vignette at \url{https://github.com/statOmics/saseR/blob/main/vignettes/Vignette.Rmd} and the saseR paper: Segers, A. et al. (2023). Juggling offsets unlocks RNA-seq tools for fast scalable differential usage, aberrant splicing and expression analyses. bioRxiv. \url{https://doi.org/10.1101/2023.06.29.547014}.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("saseR") Details
| Maintainer | Alexandre Segers <Alexandre.segers@ugent.be> |
| Author | Alexandre Segers [aut, cre], Jeroen Gilis [ctb], Mattias Van Heetvelde [ctb], Elfride De Baere [ctb], Lieven Clement [ctb] |
| License | Artistic-2.0 |
| URL | https://github.com/statOmics/saseR, https://doi.org/10.1101/2023.06.29.547014 |
| Bug Reports | https://github.com/statOmics/saseR/issues |
| Downloads rank | 181 |
| Source branch | RELEASE_3_23 |
| biocViews | AlternativeSplicing, DifferentialExpression, DifferentialSplicing, GeneExpression, RNASeq, Regression, Sequencing, Software |
Documentation
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Dependencies
Depends: R (>= 4.3.0)
Imports: ASpli, BiocGenerics, BiocParallel, data.table, DESeq2, dplyr, edgeR, GenomicAlignments, GenomicFeatures, GenomicRanges, igraph, IRanges, limma, methods, MASS, MatrixGenerics, S4Vectors, stats, SummarizedExperiment, parallel, PRROC