Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data.
Ontology highlight
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 .
SUBMITTER: Delomas TA
PROVIDER: S-EPMC10623847 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
Publications
Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data.
Delomas Thomas A TA Willis Stuart C SC
BMC bioinformatics 20231103 1
<h4>Background</h4>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.<h4>Results</h4>We developed new methods for estimating microhaplotype allele frequency from low-coverage whole genome sequence and poo ...[more]
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