recipe bioconductor-splicewiz

Easy, optimized, and accurate alternative splicing analysis in R






Reads and fragments aligned to splice junctions can be used to quantify alternative splicing events (ASE). However, overlapping ASEs can confound their quantification. SpliceWiz quantifies ASEs, calculating percent-spliced-in (PSI) using junction reads, and intron retention using IRFinder-based quantitation. Novel filters identify ASEs that are relatively less confounded by overlapping events, whereby PSIs can be calculated with higher confidence. SpliceWiz is ultra-fast, using multi-threaded processing of BAM files. It can be run using a graphical user or command line interfaces. GUI-based interactive visualization of differential ASEs, including novel group-based RNA-seq coverage visualization, simplifies short-read RNA-seq analysis in R.

package bioconductor-splicewiz

(downloads) docker_bioconductor-splicewiz



depends bioconductor-annotationhub:


depends bioconductor-biocfilecache:


depends bioconductor-biocgenerics:


depends bioconductor-biocparallel:


depends bioconductor-biostrings:


depends bioconductor-bsgenome:


depends bioconductor-delayedarray:


depends bioconductor-delayedmatrixstats:


depends bioconductor-genefilter:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicranges:


depends bioconductor-hdf5array:


depends bioconductor-iranges:


depends bioconductor-nxtirfdata:


depends bioconductor-ompbam:


depends bioconductor-rhdf5:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends bioconductor-zlibbioc:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-data.table:

depends r-dt:

depends r-fst:

depends r-ggplot2:

depends r-heatmaply:

depends r-htmltools:

depends r-magrittr:

depends r-matrixstats:

depends r-patchwork:

depends r-pheatmap:

depends r-plotly:

depends r-progress:

depends r-r.utils:

depends r-rcolorbrewer:

depends r-rcpp:


depends r-rcppprogress:

depends r-rhandsontable:

depends r-rvest:

depends r-scales:

depends r-shiny:

depends r-shinydashboard:

depends r-shinyfiles:

depends r-shinywidgets:

depends r-stringi:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-splicewiz

and update with::

   mamba update bioconductor-splicewiz

To create a new environment, run:

mamba create --name myenvname bioconductor-splicewiz

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-splicewiz/tags`_ for valid values for ``<tag>``)

Download stats