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Abstract BackgroundLow-depth sequencing allows researchers to increase sample size at the expense of lower accuracy. To incorporate uncertainties while maintaining statistical power, we introduce to analyze population structure of low-depth sequencing data. ResultsThe method optimizes the choice of nonlinear transformations of dosages to maximize the Ky Fan norm of the covariance matrix. The transformation incorporates the uncertainty in calling between heterozygotes and the common homozygotes for loci having a rare allele and is more linear when both variants are common. ConclusionsWe apply to samples from two indigenous Siberian populations and reveal hidden population structure accurately using only a single chromosome. The package is available onhttps://github.com/yiwenstat/MCPCA_PopGen.
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angsd ‐wrapper: utilities for analysing next‐generation sequencing data
Abstract High‐throughput sequencing has changed many aspects of population genetics, molecular ecology and related fields, affecting both experimental design and data analysis. The software packageangsdallows users to perform a number of population genetic analyses on high‐throughput sequencing data.angsduses probabilistic approaches which can directly make use of genotype likelihoods; thus,SNPcalling is not required for comparative analyses. This takes advantage of all the sequencing data and produces more accurate results for samples with low sequencing depth. Here, we presentangsd‐wrapper, a set of wrapper scripts that provides a user‐friendly interface for runningangsdand visualizing results.angsd‐wrapper supports multiple types of analyses including estimates of nucleotide sequence diversity neutrality tests, principal component analysis, estimation of admixture proportions for individual samples and calculation of statistics that quantify recent introgression.angsd‐wrapper also provides interactive graphing ofangsdresults to enhance data exploration. We demonstrate the usefulness ofangsd‐wrapper by analysing resequencing data from populations of wild and domesticatedZea.angsd‐wrapper is freely available fromhttps://github.com/mojaveazure/angsd-wrapper.
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- Award ID(s):
- 1339393
- PAR ID:
- 10201379
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Molecular Ecology Resources
- Volume:
- 16
- Issue:
- 6
- ISSN:
- 1755-098X
- Format(s):
- Medium: X Size: p. 1449-1454
- Size(s):
- p. 1449-1454
- Sponsoring Org:
- National Science Foundation
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