Assessing population allele frequency differences using low-depth sequencing data

Sequencing-based methods are increasingly being used for genetic studies. Genotypes derived from the sequence data are sometimes assigned incorrectly, due to having no reads for one of the alleles.This is particularly the case when the data has low sequencing depth. Here, we develop a correction that can be applied to both a measure and a test for the population differentiation metric F<sub>ST </sub>when considering populations as a fixed effect, to account for this incomplete genotyping. It is shown that the measure of differentiation is not influenced much by this correction in reasonably sized studies but that significance testing is too liberal without the correction. This correction will allow appropriate inference in population studies.

Institutions

Publication Details

Journal
AgResearch
Published
2025-08-13
DOI
https://doi.org/10.57935/agr.29897474
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing population allele frequency differences using low-depth sequencing data

AgResearch
Genetic Associations and Epidemiology
article

Assessing population allele frequency differences using low-depth sequencing data

article en

Abstract

Sequencing-based methods are increasingly being used for genetic studies. Genotypes derived from the sequence data are sometimes assigned incorrectly, due to having no reads for one of the alleles.This is particularly the case when the data has low sequencing depth. Here, we develop a correction that can be applied to both a measure and a test for the population differentiation metric F<sub>ST </sub>when considering populations as a fixed effect, to account for this incomplete genotyping. It is shown that the measure of differentiation is not influenced much by this correction in reasonably sized studies but that significance testing is too liberal without the correction. This correction will allow appropriate inference in population studies.

AgResearch
AgResearch (NZ)
Openalex Percentile: Top 47%
Genetic Associations and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.