We present a new method and software tool called that applies a pangenome index to the problem of inferring genotypes from short-read sequencing data. The method uses a novel indexing structure called the marker array. Using the marker array, we can genotype variants with respect from large panels like the 1000 Genomes Project while reducing the reference bias that results when aligning to a single linear reference. can infer accurate genotypes in less time and memory compared to existing graph-based methods. The method is implemented in the open source software tool available at
Best practices for genotype imputation from low‐coverage sequencing data in natural populations
Monitoring genetic diversity in wild populations is a central goal of ecological and evolutionary genetics and is critical for conservation biology. However, genetic studies of nonmodel organisms generally lack access to species‐specific genotyping methods (e.g. array‐based genotyping) and must instead use sequencing‐based approaches. Although costs are decreasing, high‐coverage whole‐genome sequencing (WGS), which produces the highest confidence genotypes, remains expensive. More economical reduced representation sequencing approaches fail to capture much of the genome, which can hinder downstream inference. Low‐coverage WGS combined with imputation using a high‐confidence reference panel is a cost‐effective alternative, but the accuracy of genotyping using low‐coverage WGS and imputation in nonmodel populations is still largely uncharacterized. Here, we empirically tested the accuracy of low‐coverage sequencing (0.1–10×) and imputation in two natural populations, one with a large (
- NSF-PAR ID:
- 10444672
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Molecular Ecology Resources
- ISSN:
- 1755-098X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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https://github.com/yiwenstat/MCPCA_PopGen .
