Dr Eric Fauman, senior scientific director of integrative biology group within Pfizer's internal medicine research unit will join us on Friday 11/5 12pm to 1pm to give a talk at the student brown bag/CSG meeting. Dr Fauman's talk will be followed by a lunch Q&A session where students can network with Dr Fauman and learn about industrial experience at Pfizer. Toward a gold standard SNP to gene set Genome-wide association studies have been hugely successful in identifying thousands of genomic loci reproducibly associated with a wide-variety of human phenotypes. However, elucidating the full mechanism by which any particular variant impacts a particular trait has proven to be an extraordinarily difficult task. In order to advance our understanding of the genetic architecture of human traits in general and the rules linking variants to traits, the International Common Disease Alliance commissioned a team to assemble a large and diverse collection of highly curated causal genes. I will describe our initial collection of over 1000 manually curated gene-trait assertions and an extensible and transparent framework to grow this collection over time. We hope that this collection will be useful to researchers reviewing GWAS findings as well as those looking to improve methods for automated SNP to gene mapping.
Mukai Wang, wangmk@umich.eduToward a gold standard SNP to gene set
Biostatistics Student Brown Bag with Dr. Eric Fauman, Pfizer
November 5, 2021
12:00 pm - 1:00 pm
1020 SPH II
1415 Washington Heights
Ann Arbor, MI 48109-2029
Contact Information: Mukai Wang, wangmk@umich.edu
More Information & Registration
Dr Eric Fauman, senior scientific director of integrative biology group within Pfizer's internal medicine research unit will join us on Friday 11/5 12pm to 1pm to give a talk at the student brown bag/CSG meeting. Dr Fauman's talk will be followed by a lunch Q&A session where students can network with Dr Fauman and learn about industrial experience at Pfizer. Toward a gold standard SNP to gene set Genome-wide association studies have been hugely successful in identifying thousands of genomic loci reproducibly associated with a wide-variety of human phenotypes. However, elucidating the full mechanism by which any particular variant impacts a particular trait has proven to be an extraordinarily difficult task. In order to advance our understanding of the genetic architecture of human traits in general and the rules linking variants to traits, the International Common Disease Alliance commissioned a team to assemble a large and diverse collection of highly curated causal genes. I will describe our initial collection of over 1000 manually curated gene-trait assertions and an extensible and transparent framework to grow this collection over time. We hope that this collection will be useful to researchers reviewing GWAS findings as well as those looking to improve methods for automated SNP to gene mapping.