Mentors: Kiran Garimella & Mark DePristo, Genetic Analysis and Sequencing Group
High rates of most of the common diseases in the United States, including diabetes, early onset heart attacks, and stroke, can be partly attributed to the individuals’ genetic predisposition. Treatments for many such diseases succeed only in delaying the fatal symptoms. One approach to better understand the fundamental biology of these conditions is to discover genetic variations in the genome with which they are associated. The 1000 Genomes Project is an international collaboration, of which the Broad is a member, whose goal it is to catalog all of the genetic variation in the human genome with the hope that this high-resolution genomic map will empower disease association studies.
Michael and the Genome Sequencing & Analysis Group within Medical & Population Genetics developed statistical methods to identify and remove false positive Single Nucleotide Polymorphisms (SNPs) called by the high-throughput sequencing machines at the Broad. These filters characterized SNP calls as false positives. By filtering the final “gold standard” set of SNPs, the group ensured that more of the variants sent for validation would eventually be used in disease association studies, further empowering their ability to detect genetic causes of disease.
"My summer at the Broad has given me real perspective into the life of a research scientist in the young field of genomics. Everyone involved in my success, from my mentor to the SRPG staff to the other students, has bettered me in some way. Being surrounded by such dedicated and passionate people has inspired me to keep looking for the next big idea in science."
Michael Melgar, a senior at MIT majoring in physics, developed statistical methods to filter out false positive SNPs from calls made by high-throughput sequencers for the 1000 Genomes Project.