Browsing by Author "Philippakis, Anthony"

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    FAVOR: functional annotation of variants online resource and annotator for variation across the human genome
    (Oxford University Press, 2023) Zhou, Hufeng; Arapoglou, Theodore; Li, Xihao; Li, Zilin; Zheng, Xiuwen; Moore, Jill; Asok, Abhijith; Kumar, Sushant; Blue, Elizabeth E.; Buyske, Steven; Cox, Nancy; Felsenfeld, Adam; Gerstein, Mark; Kenny, Eimear; Li, Bingshan; Matise, Tara; Philippakis, Anthony; Rehm, Heidi L.; Sofia, Heidi J.; Snyder, Grace; NHGRI Genome Sequencing Program Variant Functional Annotation Working Group; Weng, Zhiping; Neale, Benjamin; Sunyaev, Shamil R.; Lin, Xihong; Biostatistics, School of Public Health
    Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations play a critical role in WGS analysis, result interpretation, and prioritization of disease- or trait-associated causal variants. Existing functional annotation databases have limited scope to perform online queries and functionally annotate the genotype data of large biobank-scale WGS studies. We develop the Functional Annotation of Variants Online Resources (FAVOR) to meet these pressing needs. FAVOR provides a comprehensive multi-faceted variant functional annotation online portal that summarizes and visualizes findings of all possible nine billion single nucleotide variants (SNVs) across the genome. It allows for rapid variant-, gene- and region-level queries of variant functional annotations. FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient. FAVOR and FAVORannotator are available at https://favor.genohub.org.
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    STAAR workflow: a cloud-based workflow for scalable and reproducible rare variant analysis
    (Oxford University Press, 2022) Gaynor, Sheila M.; Westerman, Kenneth E.; Ackovic, Lea L.; Li, Xihao; Li, Zilin; Manning, Alisa K.; Philippakis, Anthony; Lin, Xihong; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Summary: We developed the variant-Set Test for Association using Annotation infoRmation (STAAR) workflow description language (WDL) workflow to facilitate the analysis of rare variants in whole genome sequencing association studies. The open-access STAAR workflow written in the WDL allows a user to perform rare variant testing for both gene-centric and genetic region approaches, enabling genome-wide, candidate and conditional analyses. It incorporates functional annotations into the workflow as introduced in the STAAR method in order to boost the rare variant analysis power. This tool was specifically developed and optimized to be implemented on cloud-based platforms such as BioData Catalyst Powered by Terra. It provides easy-to-use functionality for rare variant analysis that can be incorporated into an exhaustive whole genome sequencing analysis pipeline. Availability and implementation: The workflow is freely available from https://dockstore.org/workflows/github.com/sheilagaynor/STAAR_workflow.