Genomic Association
Genomic associations can help understand the underlying biology of complex traits, and the development of novel drug targets for complex diseases.
We have developed a novel computational framework for identifying genomic associations for complex traits. Our modeling approach achieves higher detection power and mapping precision by better accounting for linkage disequilibrium among markers, taking advantage of the rapid accumulation of functional marker information in biological databases, and availability of large independently collected genotype and phenotype data sets for a range of complex traits.
If you want to use our computational framework for identifying genomic associations we have provided examples in R Tutorials. Further details about the statistical models and methods we have used for identifying genomic associations can be found in QG Notes.
GACT database
Below we provide a database of Genomic Associations for Complex Traits (GACT) that are linked to a range of genomic features (such as genes, gene and sequence ontologies, biological pathways, protein and chemical complexes) to further facilitate biological interpretation and novel discoveries. Click on the links below to see data tables for different genomic feature associations.