Bibliographic Details
| Title: |
PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data |
| Authors: |
Elizabeth Wohler, Renan Martin, Sean Griffith, Eliete da S. Rodrigues, Corina Antonescu, Jennifer E. Posey, Zeynep Coban-Akdemir, Shalini N. Jhangiani, Kimberly F. Doheny, James R. Lupski, David Valle, Ada Hamosh, Nara Sobreira |
| Source: |
Orphanet Journal of Rare Diseases, Vol 16, Iss 1, Pp 1-10 (2021) |
| Publisher Information: |
BMC, 2021. |
| Publication Year: |
2021 |
| Collection: |
LCC:Medicine |
| Subject Terms: |
PhenoDB, GeneMatcher, VariantMatcher, Data sharing, Genomic data, Medicine |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1750-1172 |
| Relation: |
https://doaj.org/toc/1750-1172 |
| DOI: |
10.1186/s13023-021-01916-z |
| Access URL: |
https://doaj.org/article/4318a9ec0d084d8d8a388f43495e19c1 |
| Accession Number: |
edsdoj.4318a9ec0d084d8d8a388f43495e19c1 |
| Database: |
Directory of Open Access Journals |
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