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Combining probabilistic alignments with read pair information improves accuracy of split-alignments.
Shrestha, Anish M S; Yoshikawa, Naruki; Asai, Kiyoshi.
Afiliación
  • Shrestha AMS; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba, Japan.
  • Yoshikawa N; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba, Japan.
  • Asai K; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba, Japan.
Bioinformatics ; 34(21): 3631-3637, 2018 11 01.
Article en En | MEDLINE | ID: mdl-29790902
Motivation: Split-alignments provide base-pair-resolution evidence of genomic rearrangements. In practice, they are found by first computing high-scoring local alignments, parts of which are then combined into a split-alignment. This approach is challenging when aligning a short read to a large and repetitive reference, as it tends to produce many spurious local alignments leading to ambiguities in identifying the correct split-alignment. This problem is further exacerbated by the fact that rearrangements tend to occur in repeat-rich regions. Results: We propose a split-alignment technique that combats the issue of ambiguous alignments by combining information from probabilistic alignment with positional information from paired-end reads. We demonstrate that our method finds accurate split-alignments, and that this translates into improved performance of variant-calling tools that rely on split-alignments. Availability and implementation: An open-source implementation is freely available at: https://bitbucket.org/splitpairedend/last-split-pe. Supplementary information: Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Genómica Tipo de estudio: Prognostic_studies Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Genómica Tipo de estudio: Prognostic_studies Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Reino Unido