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VALOR2: characterization of large-scale structural variants using linked-reads.
Karaoglanoglu, Fatih; Ricketts, Camir; Ebren, Ezgi; Rasekh, Marzieh Eslami; Hajirasouliha, Iman; Alkan, Can.
Afiliação
  • Karaoglanoglu F; Department of Computer Engineering, Bilkent University, Ankara, 06800, Turkey.
  • Ricketts C; Tri-Institutional Computational Biology & Medicine Program, Cornell University, 1300 York Ave, New York, 10065, NY, USA.
  • Ebren E; Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medicine, 1300 York Ave, New York, 10065, NY, USA.
  • Rasekh ME; Department of Computer Engineering, Bilkent University, Ankara, 06800, Turkey.
  • Hajirasouliha I; Graduate Program in Bioinformatics, Boston University, 24 Cummington Mall, Boston, 02215, MA, USA.
  • Alkan C; Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medicine, 1300 York Ave, New York, 10065, NY, USA. imh2003@med.cornell.edu.
Genome Biol ; 21(1): 72, 2020 03 19.
Article em En | MEDLINE | ID: mdl-32192518
Most existing methods for structural variant detection focus on discovery and genotyping of deletions, insertions, and mobile elements. Detection of balanced structural variants with no gain or loss of genomic segments, for example, inversions and translocations, is a particularly challenging task. Furthermore, there are very few algorithms to predict the insertion locus of large interspersed segmental duplications and characterize translocations. Here, we propose novel algorithms to characterize large interspersed segmental duplications, inversions, deletions, and translocations using linked-read sequencing data. We redesign our earlier algorithm, VALOR, and implement our new algorithms in a new software package, called VALOR2.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Software / Variação Estrutural do Genoma Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Software / Variação Estrutural do Genoma Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article