Literature DB >> 28132688

InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines.

Quan Li1, Kai Wang2.   

Abstract

In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published updated standards and guidelines for the clinical interpretation of sequence variants with respect to human diseases on the basis of 28 criteria. However, variability between individual interpreters can be extensive because of reasons such as the different understandings of these guidelines and the lack of standard algorithms for implementing them, yet computational tools for semi-automated variant interpretation are not available. To address these problems, we propose a suite of methods for implementing these criteria and have developed a tool called InterVar to help human reviewers interpret the clinical significance of variants. InterVar can take a pre-annotated or VCF file as input and generate automated interpretation on 18 criteria. Furthermore, we have developed a companion web server, wInterVar, to enable user-friendly variant interpretation with an automated interpretation step and a manual adjustment step. These tools are especially useful for addressing severe congenital or very early-onset developmental disorders with high penetrance. Using results from a few published sequencing studies, we demonstrate the utility of InterVar in significantly reducing the time to interpret the clinical significance of sequence variants.
Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ACMG; ANNOVAR; ClinVar; InterVar; clinical interpretation; genetic diagnosis; variant annotation; variant interpretation

Mesh:

Year:  2017        PMID: 28132688      PMCID: PMC5294755          DOI: 10.1016/j.ajhg.2017.01.004

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  58 in total

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Journal:  Am J Hum Genet       Date:  2013-09-19       Impact factor: 11.025

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Journal:  Nature       Date:  2013-08-11       Impact factor: 49.962

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  283 in total

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Journal:  Hum Mutat       Date:  2017-08-18       Impact factor: 4.878

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5.  Set-theory based benchmarking of three different variant callers for targeted sequencing.

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Review 6.  Genomic medicine for kidney disease.

Authors:  Emily E Groopman; Hila Milo Rasouly; Ali G Gharavi
Journal:  Nat Rev Nephrol       Date:  2018-01-08       Impact factor: 28.314

7.  Dietary modification, penetrance, and the origins of congenital malformation.

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Journal:  Proc Natl Acad Sci U S A       Date:  2020-02-18       Impact factor: 11.205

Review 8.  Practical Aspects in Genetic Testing for Cardiomyopathies and Channelopathies.

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Journal:  Clin Biochem Rev       Date:  2019-11

9.  Novel candidates of pathogenic variants of the BRCA1 and BRCA2 genes from a dataset of 3,552 Japanese whole genomes (3.5KJPNv2).

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Journal:  PLoS One       Date:  2021-01-11       Impact factor: 3.240

10.  GenIO: a phenotype-genotype analysis web server for clinical genomics of rare diseases.

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Journal:  BMC Bioinformatics       Date:  2018-01-27       Impact factor: 3.169

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