TASSEL: software for association mapping of complex traits in diverse samples

Area of Science:

• Genetics
• Bioinformatics
• Population Genetics

Background:

• Genome-wide association studies (GWAS) are crucial for high-resolution genetic mapping.
• Population and family structure often confound GWAS results, necessitating robust statistical control.
• Existing methods may not adequately address the complexities of diverse genomic data.

Purpose of the Study:

• To introduce TASSEL (Trait Analysis by aSSociation, Evolution and Linkage) software.
• To provide a tool for controlling population and family structure in association analyses.
• To facilitate high-resolution genetic mapping using natural genome diversity.

Main Methods:

• Implementation of general linear models (GLM) and mixed linear models (MLM) for structure control.
• Calculation and graphical visualization of linkage disequilibrium (LD) statistics.
• Integration of phenotypic and genotypic data, with options for data imputation and principal component analysis.

Main Results:

• TASSEL effectively controls for population and family structure in association analyses.
• The software enables graphical visualization of linkage disequilibrium for result interpretation.
• Integrated middleware facilitates database browsing and data importation.

Conclusions:

• TASSEL is a valuable tool for researchers conducting high-resolution genetic mapping.
• The software addresses key challenges in association analyses, including population structure.
• TASSEL enhances the analysis of genetic diversity and its association with traits.