PT  - JOURNAL ARTICLE
AU  - Wilson McKerrow
AU  - David Fenyö
TI  - L1EM: A tool for accurate locus specific LINE-1 RNA quantification
AID  - 10.1101/714014
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 714014
4099  - http://biorxiv.org/content/early/2019/07/24/714014.short
4100  - http://biorxiv.org/content/early/2019/07/24/714014.full
AB  - Motivation LINE-1 elements are retrotransposons that are capable of copying their sequence to new genomic 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.Contact wilson.mckerrow{at}nyulangone.org, david{at}fenyolab.org