Home Department: Computer Science
Mentor: Maya Kasowski (Pathology and Medicine - Pulmonary, Allergy & Critical Care Medicine)

"Nominating Causal Variants of Thyroid Disease with Deep Learning"

Over 12% of people in the United States will develop a thyroid condition, including hypo-/hyperthyroidism, and thyroid cancer, at some point in their lives, and these diseases can increase risk for conditions like cardiovascular disease. Despite this prevalence, research at base-pair resolution on the genetic (non-coding) variants that contribute to these diseases is limited. However, recent advances in deep-learning for genomics presents a ready opportunity for research. Jack’s project will develop and apply deep-learning pipelines to analyze GWAS and eQTL datasets to nominate candidate causal variants underlying thyroid disease risk. This work can inform further disease treatments.