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

Research output: Contribution to journalArticle

Artem Babaian, I Richard Thompson, Jake Lever, Liane Gagnier, Mohammad M Karimi, Dixie L Mager, Bonnie Berger (Editor)

Original languageEnglish
Pages (from-to)3839-3841
Number of pages3
JournalBIOINFORMATICS
Volume35
Issue number19
DOIs
Published1 Oct 2019

Bibliographical note

© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

King's Authors

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.

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