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

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 who...

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Detalles Bibliográficos
Autores principales: Delomas, Thomas A., Willis, Stuart C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623847/
https://www.ncbi.nlm.nih.gov/pubmed/37923981
http://dx.doi.org/10.1186/s12859-023-05554-z
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05554-z.