Admixture in Reference Populations: 1000 Genomes Uses African Americans in African Reference Group

Today I ran into an interesting fact about how a prolifically used catalog of population controls classifies African Americans with potential impacts on research outcomes. The 1000 Genomes Project is arguably our best common set of controls used in genomic studies. They recently finished what was termed as “Phase 1” of the project, and they have been releasing full sets… Read more »

Dr. X Discovers a Better Way to Do Genetic Research Data Analysis

Bioinformatics is a serious thing. Petabytes of data that hold the truth to the genetic underpinnings of the human species, among many others, are generated and analyzed by the world’s leading scientists every year. Here at Golden Helix, we thought that there was plenty of room to add a little humor into the bioinformatics world. Meet Dr. X. He is… Read more »

Have We Wasted 7 Years and $100 Million Dollars on GWAS Studies?

Type 2 Diabetes, Rheumatoid Arthritis, Obesity, Chrohn’s Diseases and Coronary Heart Disease are examples of common, chronic diseases that have a significant genetic component. It should be no surprise that these diseases have been the target of much genetic research. Yet over the past decade, the tools of our research efforts have failed to unravel the complete biological architecture of… Read more »

Agrigenomic Researcher at U.C. Davis, Gonzalo Rincon, DVM, and Colleagues Publish 14 Articles and Obtain 2 Patents Using SVS

Editor’s Note: This case study was written while Dr. Gonzalo Rincon was with the University of California, Davis. Dr. Rincon is now working as a Principal Investigator in Animal Genetics at Zoetis. Gonzalo Rincon, DVM is a Project Scientist in the Medrano Lab, part of the Department of Animal Science, at the University of California, Davis. While the lab works… Read more »

Why You Should Care About Segmental Duplications

My work in the GHI analytical services department gives me the opportunity to handle data from a variety of sources.  I have learned over time that every genotyping platform has its own personality.  Every time we get data from a new chip, I tend to learn something new about the quirks of genotyping technology.  I usually discover these quirks the… Read more »