Package: eisaR 1.25.3

Michael Stadler

eisaR: Exon-Intron Split Analysis (EISA) in R

Exon-intron split analysis (EISA) uses ordinary RNA-seq data to measure changes in mature RNA and pre-mRNA reads across different experimental conditions to quantify transcriptional and post-transcriptional regulation of gene expression. For details see Gaidatzis et al., Nat Biotechnol 2015. doi: 10.1038/nbt.3269. eisaR implements the major steps of EISA in R.

Authors:Michael Stadler [aut, cre], Dimos Gaidatzis [aut], Lukas Burger [aut], Charlotte Soneson [aut]

eisaR_1.25.3.tar.gz
eisaR_1.25.3.zip(r-4.7-any)eisaR_1.25.3.zip(r-4.6-any)eisaR_1.25.3.zip(r-4.5-any)
eisaR_1.25.3.tgz(r-4.6-any)eisaR_1.25.3.tgz(r-4.5-any)
eisaR_1.25.3.tar.gz(r-4.7-any)eisaR_1.25.3.tar.gz(r-4.6-any)
eisaR_1.25.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
eisaR/json (API)

# Install 'eisaR' in R:
install.packages('eisaR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fmicompbio/eisar/issues

On BioConductor:eisaR-1.25.3(bioc 3.24)eisaR-1.24.0(bioc 3.23)

transcriptiongeneexpressiongeneregulationfunctionalgenomicstranscriptomicsregressionrnaseq

7.48 score 18 stars 83 scripts 688 downloads 1 mentions 6 exports 38 dependencies

Last updated from:4d658f04bd. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE194
linux-develOK418
source / vignettesOK520
linux-releaseOK460
macos-releaseOK371
macos-oldrelOK260
windows-develOK337
windows-releaseOK304
windows-oldrelOK252
wasm-releaseOK181

Exports:exportToGtfgetFeatureRangesgetRegionsFromTxDbgetTx2GeneplotEISArunEISA

Dependencies:abindBiobaseBiocGenericsclicpp11DelayedArrayedgeRfarvergenericsGenomicRangesggplot2gluegtableIRangesisobandlabelinglatticelifecyclelimmalocfitMatrixMatrixGenericsmatrixStatsR6RColorBrewerrlangS4ArraysS4VectorsS7scalesSeqinfoSparseArraystatmodSummarizedExperimentvctrsviridisLitewithrXVector

Generating reference files for spliced and unspliced abundance estimation with alignment-free methods
Introduction | Generate feature ranges | Extract feature sequences | Generate an expanded GTF file | Generate a transcript-to-gene mapping | Session info
Rendered fromrna-velocity.Rmdusingknitr::rmarkdown

Last update: 2025-09-12
Started: 2020-03-12

Using eisaR for Exon-Intron Split Analysis (EISA)
Introduction | Installation | Preparing the annotation | Quantify RNA-seq alignments in exons and introns | Align reads | Count alignments in exons and gene bodies | Load full count tables | Run EISA conveniently | Alternative implementations of EISA | On the estimation of interactions in a split-plot design experiment | Visualize EISA results | Run EISA step-by-step | Normalization | Identify quantifiable genes | Calculate $\Delta I$, $\Delta E$ and $\Delta E - \Delta I$ | Statistical analysis | Visualize the results | Session information | References
Rendered fromeisaR.Rmdusingknitr::rmarkdown

Last update: 2025-09-12
Started: 2018-11-29