In the post-genomic era, genome-wide association studies (GWAS) have produced prolific findings on the associations between single nucleotide polymorphisms (SNPs) and various complex diseases and traits. To translate those findings into new therapeutics and drug discoveries, it is essential to understand the molecular mechanisms underlying those trait-associated SNPs, in particular given their small effect sizes and often unknown functional consequences in the genome. Since it is known that trait-associated SNPs are enriched with expression quantitative trait loci (QTLs) and QTLs underlying other types of omics traits, we propose a new method and tool -- Primo (Package in R for Integrative Multi-Omics association analysis) – to conduct integrative analysis of associations of SNPs with intermediate omics traits as well as complex traits. Primo utilizes existing omicsQTL and GWAS summary statistics from different studies. In contrast to existing methods in linking up to three sets of GWAS and QTL summary statistics, Primo can jointly analyze a moderately large number of sets of summary statistics allowing the integration of QTL statistics in multi-omics data types and in multiple tissue types or cellular contexts, with appropriate multiple testing adjustments. In contrast to meta-analysis approaches testing for overall effects, Primo exhibits great flexibility in allowing study heterogeneity, allowing sample overlap/correlations, and most importantly in identifying variants in combinations of various association patterns. See flyer for more Light refreshments for seminar guests will be served at 1:30 p.m.
Department of BiostatisticsIntegrative genomic association and mediation analysis
With Lin Chen, PhD, Associate Professor of Biostatistics - The University of Chicago
December 11, 2018
2:00 pm - 3:30 pm
1655 SPH I
1415 Washington Heights
Ann Arbor, MI 48109-2029
Sponsored by: Department of Biostatistics
Contact Information: Zhenke Wu (zhenkewu@umich.edu) & Peisong Han (peisong@umich.edu)
In the post-genomic era, genome-wide association studies (GWAS) have produced prolific findings on the associations between single nucleotide polymorphisms (SNPs) and various complex diseases and traits. To translate those findings into new therapeutics and drug discoveries, it is essential to understand the molecular mechanisms underlying those trait-associated SNPs, in particular given their small effect sizes and often unknown functional consequences in the genome. Since it is known that trait-associated SNPs are enriched with expression quantitative trait loci (QTLs) and QTLs underlying other types of omics traits, we propose a new method and tool -- Primo (Package in R for Integrative Multi-Omics association analysis) – to conduct integrative analysis of associations of SNPs with intermediate omics traits as well as complex traits. Primo utilizes existing omicsQTL and GWAS summary statistics from different studies. In contrast to existing methods in linking up to three sets of GWAS and QTL summary statistics, Primo can jointly analyze a moderately large number of sets of summary statistics allowing the integration of QTL statistics in multi-omics data types and in multiple tissue types or cellular contexts, with appropriate multiple testing adjustments. In contrast to meta-analysis approaches testing for overall effects, Primo exhibits great flexibility in allowing study heterogeneity, allowing sample overlap/correlations, and most importantly in identifying variants in combinations of various association patterns. See flyer for more Light refreshments for seminar guests will be served at 1:30 p.m.
