Drawing on the sum of human genomics experiences to identify disease causing mutations

3^rd International Conference on Genomics & Pharmacogenomics

September 21-23, 2015 San Antonio, USA

Rupert Yip

QIAGEN, USA

Posters-Accepted Abstracts: J Mol Genet Med

Abstract :

A key challenge in genome interpretation and precision medicine is the lack of an extensive, high quality, ethnically-diverse collection of human genomes as a reference set. A prospective disease-causing variant that appears to be â�?�?rareâ�? based on publicly available sequence may in fact be a polymorphism in an ethnic population under-represented in public databases. Resources such as the Exome Variant Server, the 1000 Genomes Project, and the Exome Aggregation Consortium have been immensely valuable to the community, and Kaviar combines such datasets into integrated allele frequencies, but public databases have not been funded to provide broad and deep ethnic representation. QIAGENâ�?�?s Ingenuity Variant Analysisâ�?¢ genome interpretation solution has been used to interpret hundreds of thousands of ethnically diverse human sequencing samples. However, these NGS datasets are private and most are never publicly released. The Allele Frequency Community (http:// www.allelefrequencycommunity.org) has been formed to address this interpretation need. The AFC consist of over 100k of exome/genome variants sets representing human subjects from over 100 countries. This ethnically diverse dataset has been shown in internal benchmarking studies to generate a 43% average reduction in false positive rates in causal variant identification. Combining the experience of over 100,000s of genomes analyzed and access to expert-curated scientific literature, we have been able to solve genetic cases at a rate of roughly 87%. In the future we envision more examples of genetic samples â�?�?recycledâ�?�? for studies other than their original purpose furthering the research endeavors of many more scientists.