Tree-based QTL mapping with expected local genetic relatedness matrices.
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ABSTRACT: Understanding the genetic basis of complex phenotypes is a central pursuit of genetics. Genome-wide Association Studies (GWAS) are a powerful way to find genetic loci associated with phenotypes. GWAS are widely and successfully used, but they face challenges related to the fact that variants are tested for association with a phenotype independently, whereas in reality variants at different sites are correlated because of their shared evolutionary history. One way to model this shared history is through the ancestral recombination graph (ARG), which encodes a series of local coalescent trees. Recent computational and methodological breakthroughs have made it feasible to estimate approximate ARGs from large-scale samples. Here, we explore the potential of an ARG-based approach to quantitativ
SUBMITTER: Link V
PROVIDER: S-EPMC10104234 | biostudies-literature | 2023 Apr
REPOSITORIES: biostudies-literature
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