Lab Med Qual Assur 2022; 44(4): 212-215
Published online December 31, 2022
https://doi.org/10.15263/jlmqa.2022.44.4.212
Copyright © Korean Association of External Quality Assessment Service.
Eunkyoung You1 , Jong-Ho Park2
, Chang-Hun Park3
, and Kyoung-Jin Park3
1Department of Laboratory Medicine, Inje University Busan Paik Hospital, Inje University College of Medicine, Busan; 2Clinical Genomics Center, Samsung Medical Center, Seoul; 3Department of Laboratory Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Korea
Correspondence to:Kyoung-Jin Park
Department of Laboratory Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, 158 Paryong-ro, Masanhoewon-gu, Changwon 51353, Korea
Tel +82-55-233-6099
E-mail kjpark21@skku.edu
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: The variant call format (VCF) is currently used to store information on genetic variants. Variant description from the VCF is not unique or standardized. A recent survey indicated that more than half of the clinical laboratories in Korea have not performed VCF normalization procedures in their bioinformatics pipeline during routine analysis. We evaluated the effect of variant normalization on variant nomenclature using two tools.
Methods: Two binary alignment map files (GNG-21-01 and GNG-21-04) and validated variant descriptions (single-nucleotide variations [n=51] and insertions/duplications/deletions [n=13]) were provided by the Korean Association of External Quality Assessment Service. Variant calling and annotation were performed using Torrent Suite and snpEff, respectively. The vt-normalize and Genome Analysis Toolkit (GATK) LeftAlignAndTrimVariants (LAATV) were used to evaluate the effect of VCF normalization.
Results: The accuracy of the nomenclature of un-normalized variants was 99% (63/64); one variant of NM_173630.3(RTTN): c.725_727dupGAG was incorrectly described as c.724_726dupGGA. The variant description was corrected through VCF normalization. The normalization results obtained using vt-normalize and GATK LAATV were comparable.
Conclusions: VCF normalization may not generate completely correct nomenclature but contributes to more accurate annotation of variants. VCF normalization should be introduced into bioinformatics pipelines in clinical laboratories to ensure more reliable annotations of variants.
Keywords: Variant call format, Variant, Normalization, Nomenclature
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