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Tool evaluation for the detection of variably sized indels from next generation whole genome and targeted sequencing data

Insertions and deletions (indels) in human genomes are associated with a wide range of phenotypes, including various clinical disorders. High-throughput, next generation sequencing (NGS) technologies enable the detection of short genetic variants, such as single nucleotide variants (SNVs) and indels...

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Detalles Bibliográficos
Autores principales: Wang, Ning, Lysenkov, Vladislav, Orte, Katri, Kairisto, Veli, Aakko, Juhani, Khan, Sofia, Elo, Laura L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8916674/
https://www.ncbi.nlm.nih.gov/pubmed/35176018
http://dx.doi.org/10.1371/journal.pcbi.1009269
Descripción
Sumario:Insertions and deletions (indels) in human genomes are associated with a wide range of phenotypes, including various clinical disorders. High-throughput, next generation sequencing (NGS) technologies enable the detection of short genetic variants, such as single nucleotide variants (SNVs) and indels. However, the variant calling accuracy for indels remains considerably lower than for SNVs. Here we present a comparative study of the performance of variant calling tools for indel calling, evaluated with a wide repertoire of NGS datasets. While there is no single optimal tool to suit all circumstances, our results demonstrate that the choice of variant calling tool greatly impacts the precision and recall of indel calling. Furthermore, to reliably detect indels, it is essential to choose NGS technologies that offer a long read length and high coverage coupled with specific variant calling tools.