REEV: review, evaluate and explain variants-Reference-Cited by-同舟云学术

REEV: review, evaluate and explain variants

Published:2024-05-20 Issue:W1 Volume:52 Page:W148-W158
ISSN:0305-1048
Container-title:Nucleic Acids Research
language:en
Short-container-title:

Author:

Hramyka Dzmitry¹,Sczakiel Henrike Lisa²³⁴,Zhao Max Xiaohang¹²⁵,Stolpe Oliver¹,Nieminen Mikko¹^ORCID,Adam Ronja²⁵,Danyel Magdalena²³,Einicke Lara²⁵,Hägerling René²³⁴⁶⁷^ORCID,Knaus Alexej⁸,Mundlos Stefan²⁴,Schwartzmann Sarina²,Seelow Dominik²⁵^ORCID,Ehmke Nadja²⁵,Mensah Martin Atta²⁹,Boschann Felix²³⁵,Beule Dieter¹¹⁰,Holtgrewe Manuel¹^ORCID

Affiliation:

1. Berlin Institute of Health, Core Unit Bioinformatics , Berlin , Germany

2. Institute of Medical Genetics and Human Genetics, Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin , Berlin , Germany

3. BIH Biomedical Innovation Academy, Clinician Scientist Program, Berlin Institute of Health at Charité - Universitätsmedizin Berlin , Berlin , Germany

4. RG Development & Disease, Max Planck Institute for Molecular Genetics , Berlin , Germany

5. Berlin Institute of Health , Berlin, Germany

6. Berlin Institute of Health , Berlin , Germany

7. , BIH Center for Regenerative Therapies , Berlin , Germany

8. Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn , Germany

9. BIH Biomedical Innovation Academy, Digital Clinician Scientist Program, Berlin Institute of Health at Charité - Universitätsmedizin Berlin , Berlin , Germany

10. Max Delbrück Center for Molecular Medicine in the Helmholtz Association , Berlin , Germany

Abstract

Abstract In the era of high throughput sequencing, special software is required for the clinical evaluation of genetic variants. We developed REEV (Review, Evaluate and Explain Variants), a user-friendly platform for clinicians and researchers in the field of rare disease genetics. Supporting data was aggregated from public data sources. We compared REEV with seven other tools for clinical variant evaluation. REEV (semi-)automatically fills individual ACMG criteria facilitating variant interpretation. REEV can store disease and phenotype data related to a case to use these for phenotype similarity measures. Users can create public permanent links for individual variants that can be saved as browser bookmarks and shared. REEV may help in the fast diagnostic assessment of genetic variants in a clinical as well as in a research context. REEV (https://reev.bihealth.org/) is free and open to all users and there is no login requirement.

Funder

Prof. Duska Dragun

Charité—Universitätsmedizin Berlin

Berlin Institute of Health

Alliance4Rare

BIH

German national omics data infrastructure NFDI-GHGA

Charite University Medicine Library

Publisher

Oxford University Press (OUP)

Link

https://academic.oup.com/nar/article-pdf/52/W1/W148/58436096/gkae366.pdf

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