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Activity Number:
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142
- Recent Development in Computational Biology and Bioinformatics
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Type:
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Invited
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Date/Time:
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Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Section on Statistics in Genomics and Genetics
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Abstract #314467
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Title:
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A Statistical Framework to Identify Cell Types Whose Genetically Regulated Proportions Are Associated with Complex Diseases
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Author(s):
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Wei Liu and Wenxuan Deng and Ming Chen and Zihan Dong and Biqing Zhu and Zhaolong Yu and Daiwei Tang and Hongyu Zhao*
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Companies:
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Yale University and Yale University and Yale University and Yale University and Yale University and Yale University and Yale University and Yale University
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Keywords:
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Statistical genetics;
genome wide association study;
cell type proportion;
gene expression;
single cell;
genomics
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Abstract:
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Although genome wide association studies (GWAS) have identified associations between tens of thousands of genetic variants and many complex traits, it has been challenging to infer disease mechanisms from GWAS results. Finding tissues and/or cell types relevant for a disease may facilitate the identification of functional genes and variants and the study of their roles. Here we introduce a statistical framework named cell type Wide Association Study (cWAS) that integrates genetic data with single-cell and bulk-tissue transcriptomics data to identify cell types whose genetically regulated proportions are associated with diseases or traits. Applying cWAS to GWAS results from 55 complex diseases together with single-cell data from 23 adult non-brain tissues and 13 fetal brain tissues, we found many cell types whose genetically regulated proportions are associated with many of these 55 diseases. Overall, cWAS provides a powerful approach to dissecting biological mechanisms underlying complex diseases through the implications of specific cell types that may not be revealed from other methods.
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Authors who are presenting talks have a * after their name.
