Uncovering genetic architecture and disease subtyping of complex disease based on genomic and phenotypic data
Approved Research ID: 64810
Approval date: November 26th 2020
As complex diseases are diagnosed by clinical symptoms alone nowadays, it has long been hoped that genomic information will help to improve patient stratification. However, relatively few studies have investigated the potential of using genomic data in subtyping complex diseases. We will attempt a "multi-view" approach of analyzing and subtyping diseases in which clinical and genomic information are considered simultaneously. We hypothesize that genetic information will help stratify patients into meaningful subgroups, and incorporation of other clinical and environmental data will result in further improved subtyping. This project points to a new direction of genomic data analyses that may have important translational value.
In this project, we aim to study how genomic data and neurocognitive data can be used together to suggest disease subgroups. We believe that exploring new avenues of employing genomic data for translational purposes is a valuable endeavor on top of more conventional association analyses. This project is intended to last for 3 years.