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. 2021 Jan 26;11(1):2268.
doi: 10.1038/s41598-021-82006-9.

Sharing genetic variants with the NGS pipeline is essential for effective genomic data sharing and reproducibility in health information exchange

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Sharing genetic variants with the NGS pipeline is essential for effective genomic data sharing and reproducibility in health information exchange

Jeong Hoon Lee et al. Sci Rep. .

Abstract

Genetic variants causing underlying pharmacogenetic and disease phenotypes have been used as the basis for clinical decision-making. However, due to the lack of standards for next-generation sequencing (NGS) pipelines, reproducing genetic variants among institutions is still difficult. The aim of this study is to show how many important variants for clinical decisions can be individually detected using different pipelines. Genetic variants were derived from 105 breast cancer patient target DNA sequences via three different variant-calling pipelines. HaplotypeCaller, Mutect2 tumor-only mode in the Genome Analysis ToolKit (GATK), and VarScan were used in variant calling from the sequence read data processed by the same NGS preprocessing tools using Variant Effect Predictor. GATK HaplotypeCaller, VarScan, and MuTect2 found 25,130, 16,972, and 4232 variants, comprising 1491, 1400, and 321 annotated variants with ClinVar significance, respectively. The average number of ClinVar significant variants in the patients was 769.43, 16.50% of the variants were detected by only one variant caller. Despite variants with significant impact on clinical decision-making, the detected variants are different for each algorithm. To utilize genetic variants in the clinical field, a strict standard for NGS pipelines is essential.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Workflow scheme for NGS preprocessing showing the program names, versions used, options, parameters, and additional files required.
Figure 2
Figure 2
The distribution of deleteriousness scores of genetic variants called by three different variant callers represented by boxplots.
Figure 3
Figure 3
Summary of significant variants differently called by variant callers. (a) ClinVar annotated variants. (b) The consequences of truncation mutation. (c) Variants with deleterious sift scores < 0.05. (d) Variants with deleterious PolyPhen-2 scores > 0.85. (e) Variants with deleterious CADD scores > 15.

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References

    1. Biesecker LG, Green RC. Diagnostic clinical genome and exome sequencing. N. Engl. J. Med. 2014;370:2418–2425. doi: 10.1056/NEJMra1312543. - DOI - PubMed
    1. Hewett M, et al. PharmGKB: the pharmacogenetics knowledge base. Nucleic Acids Res. 2002;30:163–165. doi: 10.1093/nar/30.1.163. - DOI - PMC - PubMed
    1. Landrum MJ, et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 2015;44:D862–D868. doi: 10.1093/nar/gkv1222. - DOI - PMC - PubMed
    1. Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 2005;6:95. doi: 10.1038/nrg1521. - DOI - PubMed
    1. Aziz N, et al. College of American Pathologists’ laboratory standards for next-generation sequencing clinical tests. Arch. Pathol. Lab. Med. 2014;139:481–493. doi: 10.5858/arpa.2014-0250-CP. - DOI - PubMed

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