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

Authors :
Thomas A. Delomas
Stuart C. Willis
Source :
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-14 (2023)
Publication Year :
2023
Publisher :
BMC, 2023.

Abstract

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 .

Details

Language :
English
ISSN :
14712105
Volume :
24
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.1084619c9e43c08b0eb5059afb211f
Document Type :
article
Full Text :
https://doi.org/10.1186/s12859-023-05554-z