Harvard Countway Library – Lahey Room (5th Floor)
10 Shattuck Street, Boston, MA 02115
Computational Methods for Dissecting Multicellular Mechanisms of Complex Diseases
Single-cell genomics technologies have enabled unbiased characterization of cell types and cellular states. However, the high-dimensional nature of this data necessitates computational and statistical methods to uncover the biological processes that shape it. In my thesis research, I developed three computational methods to explore genetic regulatory mechanisms underlying common diseases and the resulting multicellular patterns of dysfunction. In the first project, I developed a method called scITD to investigate how cellular processes across distinct cell types coordinate in disease contexts. scITD identifies sets of genes in one or more cell types that co-vary together across biological samples. Through the application of this tool to various immune-cell datasets, we uncovered highly reproducible gene expression patterns associated with autoimmune patient phenotypes. In the second project, I characterized technical artifacts prevalent in imaging-based spatial transcriptomics data. These artifacts arise from the misassignment of transcript molecules to incorrect cells. I further demonstrated how these artifacts confound downstream analyses, including differential expression and cell-cell interaction inference. To address this, I jointly developed a correction method that mitigates these artifacts, thereby uncovering novel biological insights in cancer datasets. In the third project, I introduced a computational method to unravel the mechanisms of genetic variants identified from genome-wide association study loci. This method tests whether these same genetic variants also underly changes to gene expression in specific cell types or states. Applying this tool to autoimmune and neurodegenerative datasets uncovered new SNP-gene-phenotype links and localized their effects to specific cell populations, helping to refine our understanding of these pathologies.
Thesis Supervisor:
Shamil Sunyaev, Ph.D.
Professor of Biomedical Informatics, Harvard Medical School
Thesis Committee Chair:
Alex Shalek, Ph.D.
Director, Institute for Medical Engineering and Science and Health innovation Hub, MIT
J. W. Kieckhefer Professor, Department of Chemistry, Institute for Medical Engineering & Science, and Koch Institute
Thesis Readers:
Peter Kharchenko, Ph.D.
Principal Investigator, Altos Labs
Alkes Price, Ph.D.
Professor, Department of Epidemiology, Harvard T.H. Chan School of Public Health
________________________________________________________________________________________
Zoom Invitation
Jonathan Mitchell is inviting you to a scheduled Zoom meeting
Topic: Jonathan Mitchell MEMP PhD Thesis Defense
Time: Tuesday, April 15, 2025, 1:30 PM Eastern Time (US and Canada)
Your participation is important to us: please notify hst [at] mit.edu (hst[at]mit[dot]edu), at least 3 business days in advance, if you require accommodations in order to access this event.
Join Zoom Meeting
https://mit.zoom.us/j/98447598374
Password: 937198
One tap mobile
+16465588656,,98447598374# US (New York)
+16699006833,,98447598374# US (San Jose)
Meeting ID: 984 4759 8374
US : +1 646 558 8656 or +1 669 900 6833
International Numbers: https://mit.zoom.us/u/acS3TwExj1
Join by SIP
98447598374 [at] zoomcrc.com (98447598374[at]zoomcrc[dot]com)
Join by Skype for Business
https://mit.zoom.us/skype/98447598374