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Scalable Aberrant Splicing and Expression Retrieval

Bioconductor version: Release (3.19)

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{} 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{}.

Author: Alexandre Segers [aut, cre], Jeroen Gilis [ctb], Mattias Van Heetvelde [ctb], Elfride De Baere [ctb], Lieven Clement [ctb]

Maintainer: Alexandre Segers <Alexandre.segers at>

Citation (from within R, enter citation("saseR")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Main vignette: saseR analyses HTML R Script
Reference Manual PDF


biocViews AlternativeSplicing, DifferentialExpression, DifferentialSplicing, GeneExpression, RNASeq, Regression, Sequencing, Software
Version 1.0.0
In Bioconductor since BioC 3.19 (R-4.4) (< 6 months)
License Artistic-2.0
Depends R (>= 4.3.0)
Imports ASpli, S4Vectors, BiocGenerics, GenomicFeatures, MASS, PRROC, SummarizedExperiment, edgeR, pracma, precrec, BiocParallel, DESeq2, DEXSeq, data.table, limma, methods, GenomicRanges, GenomicAlignments, rrcov, MatrixGenerics, stats, IRanges, knitr, dplyr, igraph, parallel
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Follow Installation instructions to use this package in your R session.

Source Package saseR_1.0.0.tar.gz
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macOS Binary (x86_64) saseR_1.0.0.tgz
macOS Binary (arm64) saseR_1.0.0.tgz
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