scholarly journals Variant interpretation using population databases: lessons from gnomAD

2021 ◽  
Author(s):  
Sanna Gudmundsson ◽  
Moriel Singer‐Berk ◽  
Nicholas A. Watts ◽  
William Phu ◽  
Julia K. Goodrich ◽  
...  
Keyword(s):  
Variant Interpretation ◽  
Population Databases

scholarly journals Author Correction: Transcript expression-aware annotation improves rare variant interpretation

Nature ◽  
2021 ◽  
Vol 590 (7846) ◽  
pp. E54-E54
Author(s):  
Beryl B. Cummings ◽  
◽  
Konrad J. Karczewski ◽  
Jack A. Kosmicki ◽  
Eleanor G. Seaby ◽  
...  
Keyword(s):  
Rare Variant ◽  
Transcript Expression ◽  
Variant Interpretation

Impact of proactive high-throughput functional assay data on BRCA1 variant interpretation in 3684 patients with breast or ovarian cancer

2020 ◽  
Vol 65 (3) ◽  
pp. 209-220 ◽  
Author(s):  
Hyun-Ki Kim ◽  
Eun Jin Lee ◽  
Young-Jae Lee ◽  
Jisun Kim ◽  
Yongsub Kim ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Throughput ◽  
Functional Assay ◽  
Variant Interpretation

Tailoring the ACMG/AMP sequence variant interpretation guidelines to the unique aspects of germline ACADVL variants

2021 ◽  
Vol 132 ◽  
pp. S254
Author(s):  
May Flowers ◽  
Meredith Weaver ◽  
Heather Baudet ◽  
Marzia Pasquali ◽  
Gregory Enns ◽  
...  
Keyword(s):  
Sequence Variant ◽  
Variant Interpretation

Challenges in genetic testing: clinician variant interpretation processes and the impact on clinical care

2021 ◽  
Author(s):  
Courtney Berrios ◽  
Emily A. Hurley ◽  
Laurel Willig ◽  
Isabelle Thiffault ◽  
Carol Saunders ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Clinical Care ◽  
Variant Interpretation ◽  
The Impact

scholarly journals ClinVar Is a Critical Resource to Advance Variant Interpretation

2017 ◽  
Vol 22 (12) ◽  
pp. 1562-1562 ◽  
Author(s):  
Heidi L. Rehm ◽  
Steven M. Harrison ◽  
Christa L. Martin
Keyword(s):  
Variant Interpretation ◽  
Critical Resource

scholarly journals VIP-HL: Semi-automated ACMG/AMP variant interpretation platform for genetic hearing loss

2020 ◽  
Author(s):  
Jiguang Peng ◽  
Jiale Xiang ◽  
Xiangqian Jin ◽  
Junhua Meng ◽  
Nana Song ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Expert Panel ◽  
Sequence Variant ◽  
Variant Interpretation ◽  
Web Interface ◽  
Online Tool ◽  
Genetic Hearing Loss ◽  
Genetics And Genomics ◽  
Evidence Based Guidelines ◽  
User Friendly

The American College of Medical Genetics and Genomics, and the Association for Molecular Pathology (ACMG/AMP) have proposed a set of evidence-based guidelines to support sequence variant interpretation. The ClinGen hearing loss expert panel (HL-EP) introduced further specifications into the ACMG/AMP framework for genetic hearing loss. This study developed a tool named VIP-HL, aiming to semi-automate the HL ACMG/AMP rules. VIP-HL aggregates information from external databases to automate 13 out of 24 ACMG/AMP rules specified by HL-EP, namely PVS1, PS1, PM1, PM2, PM4, PM5, PP3, BA1, BS1, BS2, BP3, BP4, and BP7. We benchmarked VIP-HL using 50 variants where 83 rules were activated by the ClinGen HL-EP. VIP-HL concordantly activated 96% (80/83) rules, significantly higher than that of by InterVar (47%; 39/83). Of 4948 ClinVar star 2+ variants from 142 deafness-related genes, VIP-HL achieved an overall variant interpretation concordance in 88.0% (4353/4948). VIP-HL is an integrated online tool for reliable automated variant classification in hearing loss genes. It assists curators in variant interpretation and provides a platform for users to share classifications with each other. VIP-HL is available with a user-friendly web interface at http://hearing.genetics.bgi.com/.

scholarly journals Variant Selection and Interpretation: An Example of Modified VarSome Classifier of ACMG Guidelines in the Diagnostic Setting

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1885
Author(s):  
Francesca Cristofoli ◽  
Elisa Sorrentino ◽  
Giulia Guerri ◽  
Roberta Miotto ◽  
Roberta Romanelli ◽  
...  
Keyword(s):  
Medical Genetics ◽  
Patient Specific ◽  
Specific Information ◽  
Variant Selection ◽  
Variant Classification ◽  
Variant Interpretation ◽  
Bioinformatics Pipeline ◽  
Different Levels ◽  
Diagnostic Setting

Variant interpretation is challenging as it involves combining different levels of evidence in order to evaluate the role of a specific variant in the context of a patient’s disease. Many in-depth refinements followed the original 2015 American College of Medical Genetics (ACMG) guidelines to overcome subjective interpretation of criteria and classification inconsistencies. Here, we developed an ACMG-based classifier that retrieves information for variant interpretation from the VarSome Stable-API environment and allows molecular geneticists involved in clinical reporting to introduce the necessary changes to criterion strength and to add or exclude criteria assigned automatically, ultimately leading to the final variant classification. We also developed a modified ACMG checklist to assist molecular geneticists in adjusting criterion strength and in adding literature-retrieved or patient-specific information, when available. The proposed classifier is an example of integration of automation and human expertise in variant curation, while maintaining the laboratory analytical workflow and the established bioinformatics pipeline.

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