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Performance assessment of variant calling pipelines using human whole exome sequencing and simulated data.
Kumaran, Manojkumar; Subramanian, Umadevi; Devarajan, Bharanidharan.
Afiliación
  • Kumaran M; Department of Bioinformatics, Aravind Medical Research Foundation, Madurai, Tamil Nadu, 625020, India.
  • Subramanian U; School of Chemical and Biotechnology, SASTRA (Deemed to be University), Thanjavur, Tamil Nadu, 613401, India.
  • Devarajan B; Department of Bioinformatics, Aravind Medical Research Foundation, Madurai, Tamil Nadu, 625020, India.
BMC Bioinformatics ; 20(1): 342, 2019 Jun 17.
Article en En | MEDLINE | ID: mdl-31208315
ABSTRACT

BACKGROUND:

Whole exome sequencing (WES) is a cost-effective method that identifies clinical variants but it demands accurate variant caller tools. Currently available tools have variable accuracy in predicting specific clinical variants. But it may be possible to find the best combination of aligner-variant caller tools for detecting accurate single nucleotide variants (SNVs) and small insertion and deletion (InDels) separately. Moreover, many important aspects of InDel detection are overlooked while comparing the performance of tools, particularly its base pair length.

RESULTS:

We assessed the performance of variant calling pipelines using the combinations of four variant callers and five aligners on human NA12878 and simulated exome data. We used high confidence variant calls from Genome in a Bottle (GiaB) consortium for validation, and GRCh37 and GRCh38 as the human reference genome. Based on the performance metrics, both BWA and Novoalign aligners performed better with DeepVariant and SAMtools callers for detecting SNVs, and with DeepVariant and GATK for InDels. Furthermore, we obtained similar results on human NA24385 and NA24631 exome data from GiaB.

CONCLUSION:

In this study, DeepVariant with BWA and Novoalign performed best for detecting accurate SNVs and InDels. The accuracy of variant calling was improved by merging the top performing pipelines. The results of our study provide useful recommendations for analysis of WES data in clinical genomics.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Simulación por Computador / Polimorfismo de Nucleótido Simple / Secuenciación del Exoma Tipo de estudio: Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Simulación por Computador / Polimorfismo de Nucleótido Simple / Secuenciación del Exoma Tipo de estudio: Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: India