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.
Original language | English (US) |
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Article number | 52 |
Journal | Genome biology |
Volume | 19 |
Issue number | 1 |
DOIs | |
State | Published - Apr 12 2018 |
All Science Journal Classification (ASJC) codes
- Ecology, Evolution, Behavior and Systematics
- Genetics
- Cell Biology