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Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications


High-throughput DNA sequencing technology has transformed genetic research and is starting to make an impact on clinical practice. However, analyzing high-throughput sequencing data remains challenging, particularly in clinical settings where accuracy and turnaround times are critical. We present a new approach to this problem, implemented in a software package called Platypus. Platypus achieves high sensitivity and specificity for SNPs, indels and complex polymorphisms by using local de novo assembly to generate candidate variants, followed by local realignment and probabilistic haplotype estimation. It is an order of magnitude faster than existing tools and generates calls from raw aligned read data without preprocessing. We demonstrate the performance of Platypus in clinically relevant experimental designs by comparing with SAMtools and GATK on whole-genome and exome-capture data, by identifying de novo variation in 15 parent-offspring trios with high sensitivity and specificity, and by estimating human leukocyte antigen genotypes directly from variant calls.

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Figure 1: Simplified flow diagram of the integrated calling algorithm.
Figure 2: Size distribution of indel calls in the NA12878 trio.
Figure 3: Genotypes of the HLA-A, HLA-B and HLA-C loci at two- and four-digit resolution.


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This study was funded by Biotechnology and Biological Sciences Research Council (BBSRC) grant BB/I02593X/1 (G.L., G.M., A.R. and H.P.), by Wellcome Trust grants 102731/Z/13/Z (A.O.M.W. and S.R.F.T.), 089250/Z/09/Z (I.M.) and 090532/Z/09/Z (G.M., G.L. and A.R.), and by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre Programme. The views expressed are those of the authors and not necessarily those of the National Health Service (NHS), NIHR or the UK Department of Health.

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Authors and Affiliations




A.R. developed Platypus. A.R., H.P., I.M., Z.I. and G.L. contributed code and algorithms. A.R., H.P. and G.L. analyzed data. H.P., S.R.F.T. and A.O.M.W. performed validation experiments. WGS500 contributed data. A.O.M.W., G.M. and G.L. wrote the manuscript. G.L. initiated and led the project.

Corresponding author

Correspondence to Gerton Lunter.

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Competing interests

G.M. and G.L. are cofounders and shareholders of Genomics, Ltd. A.R. is currently employed by Genomics, Ltd. The other authors declare no competing financial interests.

Additional information

A list of members and affiliations appears in the Supplementary Note.

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Supplementary Text and Figures

Supplementary Figures 1–5, Supplementary Tables 1–6 and Supplementary Note. (PDF 13583 kb)

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Rimmer, A., Phan, H., Mathieson, I. et al. Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nat Genet 46, 912–918 (2014).

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