Proximity Search Method for Mining Biomedical and Genomic Information

The human face is an important part of the human body. Finding SNPs associated with its different regions can open doors to deeper understanding of different genetic diseases affecting the face, improve genotype-to-phenotype analysis for forensics, etc. In this work we propose a process for constructing a panel of SNPs associated with the human face leveraging a database of published work on different regions of the face and applying proximity search to ensure relevant selections of publications. We validate the process by selecting top SNPs ranked using standard metrics to make predictions on human biogeographical ancestry at the continent level. Although our process makes no assumptions on ancestry informativeness of SNPs, our panel, grouped by chromosomes, performs comparatively well at the task of ancestry classification. Our results highlight genes/chromosomes that promise better discriminative power to help those under resource constraint focus on only a few genes/chromosomes for further analyses.