期刊
BIOINFORMATICS
卷 36, 期 4, 页码 1167-1173出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btz724
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- National Institutres of Health National Institute on Aging [P01AG051449]
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 LINE-1 RNA at specific loci and to separate transcripts with protein coding capability from other sources of LINE-1 RNA. Results: We provide a tool, L1EM 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 L1EM on simulated data and against long read sequencing from HEK cells.
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