A framework for detecting noncoding rare variant associations of large-scale whole-genome sequencing studies

Abstract

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare variants’ (RVs) associations with complex human traits. Variant set analysis is a powerful approach to study RV association, and a key component of it is constructing RV sets for analysis. However, existing methods have limited ability to define analysis units in the noncoding genome. Furthermore, there is a lack of robust pipelines for comprehensive and scalable noncoding RV association analysis. Here we propose a computationally-efficient noncoding RV association-detection framework that uses STAAR (variant-set test for association using annotation information) to group noncoding variants in gene-centric analysis based on functional categories. We also propose SCANG (scan the genome)-STAAR, which uses dynamic window sizes and incorporates multiple functional annotations, in a non-gene-centric analysis. We furthermore develop STAARpipeline to perform flexible noncoding RV association analysis, including gene-centric analysis as well as fixed-window-based and dynamic-window-based non-gene-centric analysis. We apply STAARpipeline to identify noncoding RV sets associated with four quantitative lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several noncoding RV associations in an additional 9,123 TOPMed samples.

FAVOR: Functional Annotation of Variants Online Resource and Annotator for Variation across the Human Genome

“…First, it provides fast query and simultaneous retrieval of genotype and matched functional annotation data defined by flexible filtering criteria. Second, it is convenient to integrate an aGDS file into functionally informed downstream analysis pipelines, such as STAARpipeline for rare variant association analysis (13). Third, it is also highly storage-efficient for genotype and functional annotation data.…”

“…A variety of functional annotations have been developed to measure multiple aspects of biological functionality of variants, including protein function (15)(16)(17), conservation (18,19), epigenetics (20,21), spatial genomics (22,23), network biology (24), mappability (25), local nucleotide diversity (26) and integrative composite annotations (4,(27)(28)(29). These annotations have successfully prioritized plausible causal variants of underlying GWAS signals according to their functional impact in experimental studies following GWAS findings (5,30), localizing causal variants in fine-mapping studies (4,8), partitioning heritability in GWAS (6), predicting genetic risk (6,7,9), and improving rare variant (RV) analysis of WGS association studies (12)(13)(14)31). For example, large-scale WGS/WES studies (1,3,32,33) assess the associations between complex diseases/traits and coding and non-coding rare variants across the genome.…”

“…For example, large-scale WGS/WES studies (1,3,32,33) assess the associations between complex diseases/traits and coding and non-coding rare variants across the genome. The recently developed STAAR method incorporates multi-faceted variant functional annotations to boost the power of rare variant association tests in WGS/WES studies (12)(13)(14).…”

“…Existing functional annotation databases and tools are not scalable for functionally annotating a massive number of variants in large-scale WGS/WES studies. Moreover, few of the currently available functional annotation tools can provide organized output in a format that is both storage efficient and ready to be used in downstream statistical genetic analyses, such as fine-mapping (4,11), heritability (6), rare-variants association tests (13,14). There is a pressing community need to develop a convenient and comprehensive functional annotation tool that annotates any WGS study dataset at scale and generates a functionally annotated genotype file in an organized and compressed format, that can be readily integrated into the downstream analysis.…”

“…Variant functional annotation represents a powerful and effective approach to leveraging functional information from many different bioinformatics sources to elucidate the multi-faceted functions of genetic variants for a wide range of analyses of WGS/WES studies and Genome-Wide Association Studies (GWAS) (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14). A variety of functional annotations have been developed to measure multiple aspects of biological functionality of variants, including protein function (15)(16)(17), conservation (18,19), epigenetics (20,21), spatial genomics (22,23), network biology (24), mappability (25), local nucleotide diversity (26) and integrative composite annotations (4,(27)(28)(29).…”