LIONS: analysis suite for detecting and quantifying transposable element initiated transcription from RNA-seq

Bioinformatics
Artem BabaianDixie L Mager

Abstract

Transposable elements (TEs) influence the evolution of novel transcriptional networks yet the specific and meaningful interpretation of how TE-derived transcriptional initiation contributes to the transcriptome has been marred by computational and methodological deficiencies. We developed LIONS for the analysis of RNA-seq data to specifically detect and quantify TE-initiated transcripts. Source code, container, test data and instruction manual are freely available at www.github.com/ababaian/LIONS. Supplementary data are available at Bioinformatics online.

References

Oct 11, 2003·Trends in Genetics : TIG·Louie N van de LagemaatPatrik Medstrand
Jun 7, 2008·Bioinformatics·Andrew B ConleyI King Jordan
Apr 21, 2009·Nature Genetics·Geoffrey J FaulknerPiero Carninci
Aug 22, 2012·Annual Review of Genetics·Rita RebolloDixie L Mager
Nov 28, 2012·Genome Biology·David Kelley, John Rinn
Nov 22, 2016·Nature Reviews. Genetics·Edward B ChuongCédric Feschotte
Dec 17, 2016·Mobile DNA·Artem Babaian, Dixie L Mager

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Citations

Jun 25, 2020·Nature Reviews. Genetics·Sophie Lanciano, Gael Cristofari
Feb 23, 2020·Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences·Kathryn O'NeillMolly Gale Hammell
May 6, 2020·International Journal of Molecular Sciences·Federica MarascaBeatrice Bodega
Oct 17, 2020·Genes & Development·Bhavana TiwariJohn M Abrams
Jul 31, 2021·Briefings in Bioinformatics·Amarinder Singh ThindBruce Ashford

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