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SQUID: transcriptomic structural variation detection from RNA-seq

Author:
Ma, Cong, Shao, Mingfu, Kingsford, Carl
Source:
Genome biology 2018 v.19 no.1 pp. 52
ISSN:
1474-760X
Subject:
algorithms, genes, models, neoplasms, sequence analysis, transcriptomics
Abstract:
Transcripts are frequently modified by structural variations, which lead to fused transcripts of either multiple genes, known as a fusion gene, or a gene and a previously non-transcribed sequence. Detecting these modifications, called transcriptomic structural variations (TSVs), especially in cancer tumor sequencing, is an important and challenging computational problem. We introduce SQUID, a novel algorithm to predict both fusion-gene and non-fusion-gene TSVs accurately from RNA-seq alignments. SQUID unifies both concordant and discordant read alignments into one model and doubles the precision on simulation data compared to other approaches. Using SQUID, we identify novel non-fusion-gene TSVs on TCGA samples.
Agid:
5929233