PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data

Elizabeth Wohler(Johns Hopkins University), Renan Paulo Martin(Johns Hopkins University), Sean Griffith(Johns Hopkins University), Eliete da S. Rodrigues(Johns Hopkins University), Corina Antonescu(Johns Hopkins University), Jennifer E. Posey(Baylor College of Medicine), Zeynep Coban‐Akdemir(Baylor College of Medicine), Shalini N. Jhangiani(Baylor College of Medicine), Kimberly F. Doheny(Johns Hopkins University), James R. Lupski(Baylor College of Medicine), David Valle(Johns Hopkins University), Ada Hamosh(Johns Hopkins University), Nara Sobreira(Johns Hopkins University)
Orphanet Journal of Rare Diseases
August 18, 2021
Cited by 32Open Access
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Abstract

BACKGROUND: With the advent of whole exome (ES) and genome sequencing (GS) as tools for disease gene discovery, rare variant filtering, prioritization and data sharing have become essential components of the search for disease genes and variants potentially contributing to disease phenotypes. The computational storage, data manipulation, and bioinformatic interpretation of thousands to millions of variants identified in ES and GS, respectively, is a challenging task. To aid in that endeavor, we constructed PhenoDB, GeneMatcher and VariantMatcher. RESULTS: PhenoDB is an accessible, freely available, web-based platform that allows users to store, share, analyze and interpret their patients' phenotypes and variants from ES/GS data. GeneMatcher is accessible to all stakeholders as a web-based tool developed to connect individuals (researchers, clinicians, health care providers and patients) around the globe with interest in the same gene(s), variant(s) or phenotype(s). Finally, VariantMatcher was developed to enable public sharing of variant-level data and phenotypic information from individuals sequenced as part of multiple disease gene discovery projects. Here we provide updates on PhenoDB and GeneMatcher applications and implementation and introduce VariantMatcher. CONCLUSION: Each of these tools has facilitated worldwide data sharing and data analysis and improved our ability to connect genes to phenotypic traits. Further development of these platforms will expand variant analysis, interpretation, novel disease-gene discovery and facilitate functional annotation of the human genome for clinical genomics implementation and the precision medicine initiative.


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