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SQUID: transcriptomic structural variation detection from RNA-seq

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...

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Detalles Bibliográficos
Autores principales: Ma, Cong, Shao, Mingfu, Kingsford, Carl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896115/
https://www.ncbi.nlm.nih.gov/pubmed/29650026
http://dx.doi.org/10.1186/s13059-018-1421-5
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1421-5) contains supplementary material, which is available to authorized users.