To reduce false positives when identifying genetic variations associated with human disease through genome-wide association studies (GWAS), Dartmouth researchers have identified nine traits that are not dependent on P values to predict single nucleotide polymorphisms (SNP) reproducibility as reported in Human Genetics on October 2, 2014. Reproducibility rates of SNPs based solely on P values is low. Dartmouth authors' analysis of GWAS studies published in Human Genetics showed a 1-5 percent replication rate. "It is important to improve our ability to select SNPs for validation using a formalized process. In this paper, we propose a combination of traits that improve replication success," said first author Ivan P. Gorlov, PhD, DSC, associate professor of Community and Family Medicine, Geisel School of Medicine at Dartmouth. The team assigned a value of zero or one to nine different predictors. To compute the Replication Score (RS), one totals the individual scores for all significant predictors. The predictors include "Online Mendelian Inheritance in Man" (OMIM, a list of genetically caused diseases), receptors, kinases, growth factors, transcription factors, tissue specific, plasma membrane localization, nuclear localization and conversation index. The authors provided detailed information to construct the RS in supplementary material to the paper. An RS score … Continue reading →

Contact Information Available for logged-in reporters only Newswise The Gordon and Betty Moore Foundation today announced the University of Chicagos Matthew Stephens as the recipient of a Moore Investigator in Data-Driven Discovery award. Stephens, a professor in statistics and human genetics, is among 14 scientists from academic institutions nationwide who will receive a total of $21 million over five years to catalyze new data-driven scientific discoveries. Stephens grant is for $1.5 million. These Moore Investigator Awards are part of a $60 million, five-year Data-Driven Discovery Initiative within the Gordon and Betty Moores Science Program. The initiativeone of the largest privately funded data scientist programs of its kindis committed to enabling new types of scientific breakthroughs by supporting interdisciplinary, data-driven researchers. Science is generating data at unprecedented volume, variety and velocity, but many areas of science dont reward the kind of expertise needed to capitalize on this explosion of information, said Chris Mentzel, program director of the Data-Driven Discovery Initiative. We are proud to recognize these outstanding scientists, and we hope these awards will help cultivate a new type of researcher and accelerate the use of interdisciplinary, data-driven science in academia. Stephens is a data scientist who develops statistical and computational … Continue reading →