E-GWAS: an ensemble-like GWAS strategy that provides effective control over false positive rates without decreasing true positives.

ABSTRACT:

Background

Genome-wide association studies (GWAS) are an effective way to explore genotype-phenotype associations in humans, animals, and plants. Various GWAS methods have been developed based on different genetic or statistical assumptions. However, no single method is optimal for all traits and, for many traits, the putative single nucleotide polymorphisms (SNPs) that are detected by the different methods do not entirely overlap due to the diversity of the genetic architecture of complex traits. Therefore, multi-tool-based GWAS strategies that combine different methods have been increasingly employed. To take this one step further, we propose an ensemble-like GWAS strategy (E-GWAS) that statistically integrates GWAS results from different single GWAS methods.

Results

E-GWA

SUBMITTER: Zhou GL 

PROVIDER: S-EPMC10320972 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature