Literature DB >> 32249310

GenoPheno: cataloging large-scale phenotypic and next-generation sequencing data within human datasets.

Alba Gutiérrez-Sacristán1, Carlos De Niz1, Cartik Kothari1, Sek Won Kong2, Kenneth D Mandl2, Paul Avillach2.   

Abstract

Precision medicine promises to revolutionize treatment, shifting therapeutic approaches from the classical one-size-fits-all to those more tailored to the patient's individual genomic profile, lifestyle and environmental exposures. Yet, to advance precision medicine's main objective-ensuring the optimum diagnosis, treatment and prognosis for each individual-investigators need access to large-scale clinical and genomic data repositories. Despite the vast proliferation of these datasets, locating and obtaining access to many remains a challenge. We sought to provide an overview of available patient-level datasets that contain both genotypic data, obtained by next-generation sequencing, and phenotypic data-and to create a dynamic, online catalog for consultation, contribution and revision by the research community. Datasets included in this review conform to six specific inclusion parameters that are: (i) contain data from more than 500 human subjects; (ii) contain both genotypic and phenotypic data from the same subjects; (iii) include whole genome sequencing or whole exome sequencing data; (iv) include at least 100 recorded phenotypic variables per subject; (v) accessible through a website or collaboration with investigators and (vi) make access information available in English. Using these criteria, we identified 30 datasets, reviewed them and provided results in the release version of a catalog, which is publicly available through a dynamic Web application and on GitHub. Users can review as well as contribute new datasets for inclusion (Web: https://avillachlab.shinyapps.io/genophenocatalog/; GitHub: https://github.com/hms-dbmi/GenoPheno-CatalogShiny).
© The Author(s) 2020. Published by Oxford University Press.

Entities:  

Keywords:  Large-scale datasets; biobanks; catalog; next-generation sequencing data; phenotypic data; precision medicine

Year:  2021        PMID: 32249310      PMCID: PMC7820848          DOI: 10.1093/bib/bbaa033

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  62 in total

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3.  Comprehensive catalog of European biobanks.

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4.  PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.

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Authors:  Christopher A Haiman; Ying Han; Ye Feng; Lucy Xia; Chris Hsu; Xin Sheng; Loreall C Pooler; Yesha Patel; Laurence N Kolonel; Erin Carter; Karen Park; Loic Le Marchand; David Van Den Berg; Brian E Henderson; Daniel O Stram
Journal:  PLoS Genet       Date:  2013-03-28       Impact factor: 5.917

10.  The FAIR Guiding Principles for scientific data management and stewardship.

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Journal:  Sci Data       Date:  2016-03-15       Impact factor: 6.444

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  4 in total

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2.  A high-throughput phenotyping algorithm is portable from adult to pediatric populations.

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3.  FAIR Genomes metadata schema promoting Next Generation Sequencing data reuse in Dutch healthcare and research.

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Review 4.  Genome interpretation using in silico predictors of variant impact.

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  4 in total

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