Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data

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Abstract

Background: Microhaplotypes have the potential to be more cost-effective than SNPs for applications that require genetic panels of highly variable loci. However, development of microhaplotype panels is hindered by a lack of methods for estimating microhaplotype allele frequency from low-coverage whole genome sequencing or pooled sequencing (pool-seq) data. Results: We developed new methods for estimating microhaplotype allele frequency from low-coverage whole genome sequence and pool-seq data. We validated these methods using datasets from three non-model organisms. These methods allowed estimation of allele frequency and expected heterozygosity at depths routinely achieved from pooled sequencing. Conclusions: These new methods will allow microhaplotype panels to be designed using low-coverage WGS and pool-seq data to discover and evaluate candidate loci. The python script implementing the two methods and documentation are available at https://www.github.com/delomast/mhFromLowDepSeq .

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APA

Delomas, T. A., & Willis, S. C. (2023). Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data. BMC Bioinformatics, 24(1). https://doi.org/10.1186/s12859-023-05554-z

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