4.7 Article

Benchmarking small-variant genotyping in polyploids

Journal

GENOME RESEARCH
Volume 32, Issue 2, Pages 403-408

Publisher

COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1101/gr.275579.121

Keywords

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Funding

  1. Wellcome Trust Genomic Medicine and Statistics PhD Program [203735/Z/16/Z]
  2. Wellcome Trust Core Award [203141/Z/16/Z]
  3. NIHR Oxford BRC
  4. Wellcome Trust [203735/Z/16/Z] Funding Source: Wellcome Trust

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Genotyping from sequencing is essential in the molecular breeding of polyploid plants. We evaluated Octopus and other tools on polyploid data sets and found that Octopus has fewer errors in genotyping compared to other methods.
Genotyping from sequencing is the basis of emerging strategies in the molecular breeding of polyploid plants. However, compared with the situation for diploids, in which genotyping accuracies are confidently determined with comprehensive benchmarks, polyploids have been neglected; there are no benchmarks measuring genotyping error rates for small variants using real sequencing reads. We previously introduced a variant calling method, Octopus, that accurately calls germline variants in diploids and somatic mutations in tumors. Here, we evaluate Octopus and other popular tools on whole-genome tetraploid and hexaploid data sets created using in silico mixtures of diploid Genome in a Bottle (GIAB) samples. We find that genotyping errors are abundant for typical sequencing depths but that Octopus makes 25% fewer errors than other methods on average. We supplement our benchmarks with concordance analysis in real autotriploid banana data sets.

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