Title |
SQUID: transcriptomic structural variation detection from RNA-seq
|
---|---|
Published in |
Genome Biology, April 2018
|
DOI | 10.1186/s13059-018-1421-5 |
Pubmed ID | |
Authors |
Cong Ma, Mingfu Shao, Carl Kingsford |
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. |
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Switzerland | 1 | 4% |
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Mendeley readers
Geographical breakdown
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Unknown | 132 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 25 | 19% |
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Other | 10 | 8% |
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Other | 21 | 16% |
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Engineering | 4 | 3% |
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