Artifact Identification in Germline Next-Generation Sequencing Bioinformatics Pipelines

Background: Bioinformatics pipelines influence putative false-positive calls (technical artifacts) in clinical germline next-generation sequencing; however, the impact of workflow updates on variant detection behavior in clinical panels remains unclear.Methods: We analyzed 114 clinical samples that were sequenced using a 4,815-gene panel.Starting with identical FASTQ files, we compared a legacy workflow (Burrows-Wheeler aligner [BWA] aln+Genome Analysis Toolkit [GATK] UnifiedGenotyper) and a modern workflow (BWA-maximal exact matches [MEM]+GATK HaplotypeCaller), aligners under a fixed caller, and callers under a fixed aligner.Putative technical artifacts were defined as recurrent variants (≥10/114 samples) that were rare (gnomAD minor allele frequency <0.001) or absent from gnomAD and the Korean reference database (K1055E).Concordance with the GIAB HG001 (NA12878) truth set was evaluated within the panel target regions that intersected with GIAB high-confidence regions.Results: The legacy workflow produced 1,691 recurrent rare/novel variants that were not reproduced by the modern workflow.The transition/ transversion ratio shifted from 3.097 to 2.393 for the same TruSight One target design, indicating workflow-dependent differences in the single nucleotide variant spectrum.Indel call counts increased 7.37-fold, reflecting a change in call yield rather than a direct improvement in accuracy.In controlled comparisons, BWA aln and FreeBayes generated more recurrent rare/novel calls than BWA-MEM/Bowtie2 and HaplotypeCaller.In the GIAB benchmark, the pipelines showed comparable concordance with a slightly higher single nucleotide polymorphism concordance in the legacy workflow and increased indel detection in the modern workflow.Conclusions: Updating the aligner-caller workflow markedly reduced recurrent rare/novel calls, consistent with technical artifacts in clinical germline panel testing.This finding highlights the importance of validating workflow updates.

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Publication Details

Journal
Journal of Laboratory Medicine and Quality Assurance
Published
2026-06-26
DOI
https://doi.org/10.15263/jlmqa.2026.48.2.46
Primary Topic
Genomics and Rare Diseases
Type
article
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article

Artifact Identification in Germline Next-Generation Sequencing Bioinformatics Pipelines

Jaewoong Lee
Journal of Laboratory Medicine and Quality Assurance
Genomics and Rare Diseases
article

Artifact Identification in Germline Next-Generation Sequencing Bioinformatics Pipelines

Jaewoong Lee
article en

Abstract

Background: Bioinformatics pipelines influence putative false-positive calls (technical artifacts) in clinical germline next-generation sequencing; however, the impact of workflow updates on variant detection behavior in clinical panels remains unclear.Methods: We analyzed 114 clinical samples that were sequenced using a 4,815-gene panel.Starting with identical FASTQ files, we compared a legacy workflow (Burrows-Wheeler aligner [BWA] aln+Genome Analysis Toolkit [GATK] UnifiedGenotyper) and a modern workflow (BWA-maximal exact matches [MEM]+GATK HaplotypeCaller), aligners under a fixed caller, and callers under a fixed aligner.Putative technical artifacts were defined as recurrent variants (≥10/114 samples) that were rare (gnomAD minor allele frequency <0.001) or absent from gnomAD and the Korean reference database (K1055E).Concordance with the GIAB HG001 (NA12878) truth set was evaluated within the panel target regions that intersected with GIAB high-confidence regions.Results: The legacy workflow produced 1,691 recurrent rare/novel variants that were not reproduced by the modern workflow.The transition/ transversion ratio shifted from 3.097 to 2.393 for the same TruSight One target design, indicating workflow-dependent differences in the single nucleotide variant spectrum.Indel call counts increased 7.37-fold, reflecting a change in call yield rather than a direct improvement in accuracy.In controlled comparisons, BWA aln and FreeBayes generated more recurrent rare/novel calls than BWA-MEM/Bowtie2 and HaplotypeCaller.In the GIAB benchmark, the pipelines showed comparable concordance with a slightly higher single nucleotide polymorphism concordance in the legacy workflow and increased indel detection in the modern workflow.Conclusions: Updating the aligner-caller workflow markedly reduced recurrent rare/novel calls, consistent with technical artifacts in clinical germline panel testing.This finding highlights the importance of validating workflow updates.

Journal of Laboratory Medicine and Quality AssuranceVol. 48(2)
The Catholic University of Korea Incheon St. Mary's Hospital (KR)
Openalex Percentile: Top 7%
Genomics and Rare Diseases
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