2026-09-19T10:46:28Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1503062023-04-01T03:47:09Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Kellis, Manolis
Tanigawa, Yosuke
Ismoldayeva, Assel
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2023-03-31T14:46:35Z
2023-03-31T14:46:35Z
2023-02
2023-02-27T18:43:14.024Z
https://hdl.handle.net/1721.1/150306
Lung cancer is a complex disease influenced by a variety of genetic and environmental factors. The germline mutations associated with the disease vary greatly between the East Asian and the European populations. We explore these differences by analyzing genome-wide association study summary statistics from European and Japanese biobanks. Using stratified linkage disequilibrium regression in conjunction wit gene expression-based and epigenetic annotations, we derive cell-types and biological processes associated with lung cancer and smoking in both populations.
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
Statistical and Computational Methods to Dissect Ancestry-Biased Germline Effects in Lung Cancer
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
unknown
unknown
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<Abstract>Lung cancer is a complex disease influenced by a variety of genetic and environmental factors. The germline mutations associated with the disease vary greatly between the East Asian and the European populations. We explore these differences by analyzing genome-wide association study summary statistics from European and Japanese biobanks. Using stratified linkage disequilibrium regression in conjunction wit gene expression-based and epigenetic annotations, we derive cell-types and biological processes associated with lung cancer and smoking in both populations.</Abstract>
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