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L1EM: A tool for accurate locus specific LINE-1 RNA quantification

By Wilson McKerrow, David Fenyƶ

Posted 24 Jul 2019
bioRxiv DOI: 10.1101/714014 (published DOI: 10.1093/bioinformatics/btz724)

Motivation: LINE-1 elements are retrotransposons that are capable of copying their sequence to new ge-nomic loci. LINE-1 derepression is associated with a number of disease states, and has the potential to cause significant cellular damage. Because LINE-1 elements are repetitive, it is difficult to quantify RNA at specific LINE-1 loci and to separate transcripts with protein coding capability from other sources of LINE-1 RNA. Results: We provide a tool, L1-EM that uses the expectation maximization algorithm to quantify LINE-1 RNA at each genomic locus, separating transcripts that are capable of generating retrotransposition from those that are not. We show the accuracy of L1-EM on simulated data and against long read sequencing from HEK cells. Availability: L1-EM is written in python. The source code along with the necessary annotations are available at https://github.com/FenyoLab/L1EM and distributed under GPLv3.

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