Computational & Statistical Tools Program
This program supports research that develops novel tools or approaches for the analysis of large-scale genetic, multi -omic, and phenomic data as it applies to mental health and related traits. The program encourages multi-disciplinary approaches spanning statistics, mathematics, physics, computer science, and engineering.
Areas of Emphasis
- Methods for increasing the power and reliability of association studies including whole-genome and genome-, exome-, epigenome-, phenome- and other ‘ome’-wide studies.
- Methods for integrating multi-omic data sets from tissues and single cells.
- Methods for integrating phenotype data spanning multiple levels (e.g., genetic variation, gene expression, electrophysiology, neuroimaging, behavior).
- Methods for robust genome-wide and brain-wide association studies.
- Methods for robust genome x phenome-wide interaction studies.
- Methods for robust genome-wide epistasis detection.
Alexander Arguello, Ph.D.
6001 Executive Blvd., Room 7200, MSC 9643