Comparison of GATK and DeepVariant by trio sequencing

Yi-Lin Lin,Pi-Chuan Chang,Ching Hsu,Wuh-Liang Hwu,Yin-Hsiu Chien,Feipei Lai,Miao-Zi Hung,Ni-Chung Lee

doi:10.1038/s41598-022-05833-4

Abstract

While next-generation sequencing (NGS) has transformed genetic testing, it generates large quantities of noisy data that require a significant amount of bioinformatics to generate useful interpretation. The accuracy of variant calling is therefore critical. Although GATK HaplotypeCaller is a widely used tool for this purpose, newer methods such as DeepVariant have shown higher accuracy in assessments of gold-standard samples for whole-genome sequencing (WGS) and whole-exome sequencing (WES), but a side-by-side comparison on clinical samples has not been performed. Trio WES was used to compare GATK (4.1.2.0) HaplotypeCaller and DeepVariant (v0.8.0). The performance of the two pipelines was evaluated according to the Mendelian error rate, transition-to-transversion (Ti/Tv) ratio, concordance rate, and pathological variant detection rate. Data from 80 trios were analyzed. The Mendelian error rate of the 77 biological trios calculated from the data by DeepVariant (3.09 ± 0.83%) was lower than that calculated from the data by GATK (5.25 ± 0.91%) (p < 0.001). DeepVariant also yielded a higher Ti/Tv ratio (2.38 ± 0.02) than GATK (2.04 ± 0.07) (p < 0.001), suggesting that DeepVariant proportionally called more true positives. The concordance rate between the 2 pipelines was 88.73%. Sixty-three disease-causing variants were detected in the 80 trios. Among them, DeepVariant detected 62 variants, and GATK detected 61 variants. The one variant called by DeepVariant but not GATK HaplotypeCaller might have been missed by GATK HaplotypeCaller due to low coverage. OTC exon 2 (139 bp) deletion was not detected by either method. Mendelian error rate calculation is an effective way to evaluate variant callers. By this method, DeepVariant outperformed GATK, while the two pipelines performed equally in other parameters.

Highlights

Whole-exome sequencing (WES) by next-generation sequencing (NGS) has become an important tool in the diagnosis of inherited d iseases[1]
The time required for variant calling was 3851 ± 253 s for GATK and 425 ± 0.6 s for DeepVariant (p = 0.046)
92,000–120,000 changes were identified for each patient

Summary

Introduction

Whole-exome sequencing (WES) by next-generation sequencing (NGS) has become an important tool in the diagnosis of inherited d iseases[1]. An increasing number of medical centers consider WES first-line genetic testing. As NGS yields tens of thousands of short-read sequences, accurate variant calling is crucial for subsequent variant prioritization. GATK HaplotypeCaller is the most widely used. Previous studies have highlighted that different variant callers generated substantial disagreement[7–9]. DeepVariant won the PrecisionFDA Truth Challenge in 2016, demonstrating a higher accuracy in single-nucleotide polymorphism (SNP) detection than G ATK6,10. There are different ways to evaluate the performance of variant callers. To evaluate variant callers on real-world data, in this study, we employed the Mendelian error rate and several other metrics to compare GATK and DeepVariant

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Conclusion