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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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MorbidGenes-Panel-v2022-02.1

Authors: Jauss, Robin-Tobias; Popp, Bernt; Platzer, Konrad; Jamra, Rami;

MorbidGenes-Panel-v2022-02.1

Abstract

Background: Identifying clinically relevant genetic variants is crucial for a fast and reliable genetic diagnosis. With exome sequencing now standard, diagnostic labs are in need of a, in principle, to-the-day-accurate list of genes associated with rare diseases. Manual curation efforts are slow and often disease specific, while efforts relying on single sources are too inaccurate and result in too many false-positive genes. Methods: We established the MorbidGenes panel based on a list of publicly available databases: OMIM, PanelApp, SysNDD, ClinVar, HGMD and GenCC. A simple logic allows inclusion of genes with sufficient evidence based on a voting algorithm. By providing an API endpoint, users can directly access the list and meta data for all relevant information on their genes of interest. Results: The panel currently includes 4,677 genes (v.2022-02.1, as of February 2022) with minimally sufficient evidence on disease causality to classify them as diagnostically relevant. Reproducible filtering and versioning allow the integration into diagnostic pipelines. In-house Implementation successfully removed false positive genes and reduced time requirements in routine exome diagnostics. The panel is updated monthly, and we will integrate novel sources on a regular basis. Conclusion: The MorbidGenes panel is a comprehensive and open overview of clinically relevant genes based on a growing list of sources. It supports genetic diagnostics labs by providing diagnostically relevant genes in a QM conform format on a monthly basis with more frequent updates planned. Once genomes are standard, diagnostically relevant non-coding regions will also be included.

Related Organizations
Keywords

Genes, Pathogenic, Diagnostics

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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