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Variations in Nomenclature of Clinical Variants between Annotation Tools.
Park, Kyoung-Jin; Park, Jong-Ho.
Afiliación
  • Park KJ; Department of Laboratory Medicine & Genetics, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, South Korea.
  • Park JH; Department of Laboratory Medicine & Genetics, Samsung Medical Center, Seoul, South Korea.
Lab Med ; 53(3): 242-245, 2022 May 05.
Article en En | MEDLINE | ID: mdl-34612497
ABSTRACT

BACKGROUND:

Accurate nomenclature of variants is an essential element for genetic diagnosis and patient care.

OBJECTIVE:

To investigate annotation differences of clinical variants between annotation tools.

METHODS:

We analyzed 218,156 clinical variants from the Human Gene Mutation Database. Multiple nomenclatures based on RefSeq transcripts were provided using ANNOVAR and snpEff.

RESULTS:

The concordance rate between ANNOVAR and snpEff was approximately 85%. Based on the Human Genome Variation Society (HGVS) nomenclature, snpEff was more accurate than ANNOVAR (coding variants, 99.3% vs 84.9%; protein variants, 94.3% vs 79.8%). When annotating each variant with ANNOVAR and snpEff, the accuracy of nomenclature was 99.5%.

CONCLUSIONS:

There were substantial differences between ANNOVAR and snpEff annotations. The findings of this study suggest that simultaneous use of multiple annotation tools could decrease nomenclature errors and contribute to providing standardized clinical reporting.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Genoma Humano Límite: Humans Idioma: En Revista: Lab Med Año: 2022 Tipo del documento: Article País de afiliación: Corea del Sur

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Genoma Humano Límite: Humans Idioma: En Revista: Lab Med Año: 2022 Tipo del documento: Article País de afiliación: Corea del Sur