Michael Mooney, PhD
ABOUT RESEARCH CODE EDUCATION

PolyGA:  A Feature Selection Tool for Polygenic Analyses

PolyGA is a Python program that performs a search to identify polygenic signatures (e.g. variant or gene sets) associated with a trait of interest. Candidate feature sets are identified by searching a gene-gene interaction network using a genetic algorithm (GA), which is guided by user-supplied expert knowledge.

Author: Michael Mooney <mooneymi at ohsu.edu>
Development Code:

github.com/mooneymi/polyga
Downloads:
  • NOTE: The following code is experimental and is not guaranteed to be free of bugs.
  • PolyGA v1.0 (includes python program, sample data, and user manual)
Documentation:
References:
  • Michael A. Mooney, Beth Wilmot, The Bipolar Genome Study, Shannon K. McWeeney. The GA and the GWAS: Using Genetic Algorithms to Search for Multi-locus Associations. IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 3, pp. 899-910, May-June 2012. PMCID: PMC3748153
Links:

evo·comp·bio