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De novo assembly and genotyping of variants using colored de Bruijn graphs

Detecting genetic variants that are highly divergent from a reference sequence remains a major challenge in genome sequencing. We introduce de novo assembly algorithms using colored de Bruijn graphs for detecting and genotyping simple and complex genetic variants in an individual or population. We p...

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Detalles Bibliográficos
Autores principales: Iqbal, Zamin, Caccamo, Mario, Turner, Isaac, Flicek, Paul, McVean, Gil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3272472/
https://www.ncbi.nlm.nih.gov/pubmed/22231483
http://dx.doi.org/10.1038/ng.1028
Descripción
Sumario:Detecting genetic variants that are highly divergent from a reference sequence remains a major challenge in genome sequencing. We introduce de novo assembly algorithms using colored de Bruijn graphs for detecting and genotyping simple and complex genetic variants in an individual or population. We provide an efficient software implementation, Cortex; the first de novo assembler capable of assembling multiple eukaryote genomes simultaneously. Four applications of Cortex are presented. First, we detect and validate both simple and complex structural variation in a high coverage human genome. Second, we identify over 3Mb of novel sequence in pooled low-coverage population sequence data from the 1000 Genomes Project. Third, we show how population information from 10 chimpanzees enables accurate variant calls without a reference sequence. Finally, we estimate classical HLA genotypes at HLA-B, the most variable gene in the human genome.