Fine-Mapping Tools : an interactive framework for dissecting disease-associated genetic loci with functional genomics data

Fine mapping causal SNPs from GWAS summary statistics is hard. Although many frame- works exist to support fine mapping, some of which leverage epigenomic contexts to increase predictive power, they fail to provide interactivity. Here, we introduce Fine-Mapping Tools (fm-tools), a framework for doing interactive and iterative fine mapping. Fm-tools provides a harmonized data store and implements a number of algorithms for fine mapping -- one of which is the custom RiVIERA-mini, an efficient Bayesian inference framework -- and exposes them via a rich API that can be plugged into a variety of services (e.g., web applications for visualization). Most importantly, fm-tools allows scientists to interactively and iteratively explore dynamically generated hypotheses, as demonstrated by a case study for celiac disease. In summary, fm-tools standardizes the way fine mapping is done, reduces the overhead of fine mapping for scientists and of algorithm development for researchers, and paves the way towards achieving real-time personalized medicine.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Nguyen, Peter H. T. (Peter Hung Trung)

Advisor dc:contributor.advisor

• Manolis Kellis.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/113121

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/113121