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FunSPU: A versatile and adaptive multiple functional annotation-based association test of whole-genome sequencing
1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Plos Genetics
|April 30, 2019
Summary
Whole-genome sequencing association studies face challenges with rare variants. A new adaptive test, FunSPU, effectively integrates multiple biological annotations to identify trait-associated genetic loci, improving power and discovery.
Area of Science:
- Genomics and Bioinformatics
- Statistical Genetics
- Complex Trait Association Analysis
Background:
- Large-scale whole-genome sequencing (WGS) projects generate vast amounts of data, but analyzing rare variants for complex traits remains challenging due to noise from neutral variants.
- Functional annotations from projects like ENCODE, Epigenomics Roadmap, and GTEx offer biological context but incorporating them effectively is difficult due to limited prior knowledge and potential for noise.
Purpose of the Study:
- To develop a versatile and adaptive statistical test, FunSPU, capable of integrating multiple biological annotations to enhance rare variant association analysis.
- To improve the power of detecting causal rare variants while mitigating the impact of non-informative annotations.
Main Methods:
- Proposed FunSPU, an adaptive test that incorporates multiple biological annotations at both the annotation and variant levels.
- Evaluated FunSPU through extensive simulations and applied it to the TWINSUK cohort (n=1,752) using WGS data and six functional annotations (CADD, RegulomeDB, FunSeq, Funseq2, GERP++, GenoSkyline).
- Replicated findings in the UK10K ALSPAC cohort (n=1,497).
Main Results:
- Identified genome-wide significant genetic loci on chromosome 19 near TOMM40 and APOC4-APOC2 associated with low-density lipoprotein (LDL) levels.
- These findings were successfully replicated in an independent cohort.
- The identified loci were missed by existing rare variant association tests that do not leverage multiple biological annotations.
Conclusions:
- FunSPU is a powerful and adaptive method for rare variant association analysis that effectively utilizes multiple functional annotations.
- The method successfully identified novel LDL-associated loci, demonstrating its utility in uncovering genetic associations missed by conventional approaches.
- An R package, FunSPU, has been developed to facilitate the application of this novel statistical test.
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