Richard Littin

Comparing Variant Call Files for Performance Benchmarking of Next-Generation Sequencing Variant Calling Pipelines

Summary To evaluate and compare the performance of variant calling methods and their confidence scores, comparisons between a test call set and a “gold standard” need to be carried out. Unfortunately, these comparisons are not straightforward with the current Variant Call Files (VCF), which are the standard output of most variant calling algorithms for high-throughput sequencing data. Comparisons of VCFs are often confounded by the different representations of indels, MNPs, and combinations thereof with SNVs in complex regions of the genome, resulting in misleading results. A variant caller is inherently a classification method designed to score putative variants with confidence scores that could permit controlling the rate of false positives (FP) or false negatives (FN) for a given application. Receiver operator curves (ROC) and the area under the ROC (AUC) are efficient metrics to evaluate a test call set versus a gold standard. However, in the case of VCF data this also requires a special accounting to deal with discrepant representations. We developed a novel algorithm for comparing variant call sets that deals with complex call representation discrepancies and through a dynamic programing method that minimizes false positives and negatives globally across the entire call sets for accurate performance evaluation of VCFs. Availability RTG Tools is implemented as a multithreaded Java application and source code is available under BSD license at: https://github.com/RealTimeGenomics/rtg-tools Contact len@realtimegenomics.com Supplementary information Supplementary data are available at Bioinformatics online.

Applying Time Warp to CPU design

This paper exemplifies the similarities in Time Warp and computer architecture concepts and terminology, and the continued trend for convergence of ideas in these two areas. Time Warp can provide a means to describe the complex mechanisms being used to allow the instruction execution window to be enlarged. Furthermore it can extend the current mechanisms, which do not scale, in a scalable manner. The issues involved in implementing Time Warp in a CPU design are also examined, and illustrated with reference to the Wisconsin Multiscalar machine and the Waikato WarpEngine. Finally the potential performance gains of such a system are briefly discussed.