Genome‐wide association studies (GWAS) have developed into a powerful and ubiquitous
tool for the investigation of complex traits. In large part, this was fueled by advances in …

This review describes the current status of genome-wide association study (GWAS) of the
major crops in maize (Zea mays L.) concentrate on performing association mapping as a …

Genome-wide association study (GWAS) and genomic prediction/selection (GP/GS) are the
two essential enterprises in genomic research. Due to the great magnitude and complexity …

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled
by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population …

Big datasets, accumulated from biomedical and agronomic studies, provide the potential to
identify genes that control complex human diseases and agriculturally important traits …

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait
associations (MTAs) using whole genome-wide variants for complex quantitative traits in …

Genome-wide association study (GWAS) has become a widely accepted strategy for
decoding genotype-phenotype associations in many species thanks to advances in next …

Association mapping (AM) is a powerful tool for fine mapping complex trait variation down to
nucleotide sequences by exploiting historical recombination events. A major problem in AM …

The mixed linear model has been widely used in genome-wide association studies (GWAS),
but its application to multi-locus GWAS analysis has not been explored and assessed. Here …

Most human diseases and agriculturally important traits are complex. Dissecting their
genetic architecture requires continued development of innovative and powerful statistical …