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

Abstract Summary 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 dev...

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Bibliographic Details
Published in:Bioinformatics 2019-10, Vol.35 (19), p.3839-3841
Main Authors: Babaian, Artem, Thompson, I Richard, Lever, Jake, Gagnier, Liane, Karimi, Mohammad M, Mager, Dixie L
Format: Article
Language:English
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Summary:Abstract Summary 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. Availability and implementation Source code, container, test data and instruction manual are freely available at www.github.com/ababaian/LIONS. Supplementary information Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btz130