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. 2015:2015:456479.
doi: 10.1155/2015/456479. Epub 2015 Oct 11.

A Comparison of Variant Calling Pipelines Using Genome in a Bottle as a Reference

Adam Cornish  1 , Chittibabu Guda  2
Affiliations

A Comparison of Variant Calling Pipelines Using Genome in a Bottle as a Reference

Adam Cornish et al. Biomed Res Int. 2015.

Abstract

High-throughput sequencing, especially of exomes, is a popular diagnostic tool, but it is difficult to determine which tools are the best at analyzing this data. In this study, we use the NIST Genome in a Bottle results as a novel resource for validation of our exome analysis pipeline. We use six different aligners and five different variant callers to determine which pipeline, of the 30 total, performs the best on a human exome that was used to help generate the list of variants detected by the Genome in a Bottle Consortium. Of these 30 pipelines, we found that Novoalign in conjunction with GATK UnifiedGenotyper exhibited the highest sensitivity while maintaining a low number of false positives for SNVs. However, it is apparent that indels are still difficult for any pipeline to handle with none of the tools achieving an average sensitivity higher than 33% or a Positive Predictive Value (PPV) higher than 53%. Lastly, as expected, it was found that aligners can play as vital a role in variant detection as variant callers themselves.

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Figures

Figure 1
Figure 1
Schematic of the data analysis pipeline used. To ensure that the highest quality alignments are created, reads are first filtered and then aligned to the human reference genome, hg19. Next, PCR duplicates are removed, reads are aligned around putative indels, and base quality scores are recalibrated. Finally, variants are called and validated against the NIST-GiaB list of variants.
Figure 2
Figure 2
Sensitivity as a function of depth for the top five pipelines. The top five pipelines are shown here with the depth of every SNV plotted against sensitivity.
Figure 3
Figure 3
Sensitivity as a function of depth for the top aligner and top variant caller. (a) Results for the depth of every SNV plotted against sensitivity for the top aligner, BWA mem, paired with every variant caller. (b) Results for the depth of every SNV plotted against sensitivity for the top variant caller, GATK UnifiedGenotyper, paired with every aligner.
Figure 4
Figure 4
The intersection of the SNVs identified by the top five pipelines.
See this image and copyright information in PMC

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