Learn how to meet the data handling challenges that Genome Wide Association Studies can create. Assure the quality of your data in an easy and automated way.
Genome Wide Association Studies, or GWAS for short, are gradually becoming more commonplace. These studies are designed to find genetic variants, or SNPs, that are correlated between Case or Control individuals. Rapid advances in the genotyping technology have dramatically increased our ability to generate ever larger amounts of data over the last year. Experiments are now being planned that measure a million SNPs across tens of thousands of samples.
This paper will briefly describe how InforSense has met some of the challenges that scientists have to solve when faced with analyzing the results from a GWA study.
Offered Free by: InforSense
See All Resources from: InforSense