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eXtasy: variant prioritization by genomic data fusion

Nature Methods volume 10, pages 1083–1084 (2013)Cite this article

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Abstract

Massively parallel sequencing greatly facilitates the discovery of novel disease genes causing Mendelian and oligogenic disorders. However, many mutations are present in any individual genome, and identifying which ones are disease causing remains a largely open problem. We introduce eXtasy, an approach to prioritize nonsynonymous single-nucleotide variants (nSNVs) that substantially improves prediction of disease-causing variants in exome sequencing data by integrating variant impact prediction, haploinsufficiency prediction and phenotype-specific gene prioritization.

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Figure 1: Receiver operating characteristic (ROC) curves comparing eXtasy and classical deleteriousness prediction scores.

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Acknowledgements

This research is supported by Research Council KU Leuven: GOA/10/09 Manet, PFV/10/016 SymBioSys, IOF 3M120274 Immunosuppressive drugs; iMinds: SBO 2013; Hercules Stichting: Hercules III PacBio RS; the Flemish Institute for Science and Technology: IWT-SB/093289, IWT-TBM Haplotyping; EU: Cost Action BM1006: NGS Data Analysis Network, FCT Neuroclinomics.

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Author notes

  1. Alejandro Sifrim and Dusan Popovic: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium

    Alejandro Sifrim, Dusan Popovic, Leon-Charles Tranchevent, Amin Ardeshirdavani, Ryo Sakai, Peter Konings, Jan Aerts, Bart De Moor & Yves Moreau

  2. iMinds Future Health Department, Leuven, Belgium

    Alejandro Sifrim, Dusan Popovic, Leon-Charles Tranchevent, Amin Ardeshirdavani, Ryo Sakai, Peter Konings, Jan Aerts, Bart De Moor & Yves Moreau

  3. Laboratory of Molecular Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium

    Joris R Vermeesch

Authors
  1. Alejandro Sifrim
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  2. Dusan Popovic
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  3. Leon-Charles Tranchevent
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  4. Amin Ardeshirdavani
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  5. Ryo Sakai
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  6. Peter Konings
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  7. Joris R Vermeesch
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  8. Jan Aerts
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  9. Bart De Moor
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  10. Yves Moreau
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Contributions

A.S., D.P. and Y.M. conceptually defined the project. A.S. and D.P. wrote the initial draft of the manuscript and performed the analyses. A.S. generated the data sets and developed the software tools. D.P. developed the benchmarks and trained the models. L.-C.T. and A.S. computed the Endeavour gene prioritizations. A.A. and A.S. developed the web tool. R.S. and J.A. advised on data visualization and visual analytics. P.K. advised on statistical concerns. J.R.V. advised on genetical concerns. All authors revised and proofread the paper. B.D.M. cosupervised the project. Y.M. supervised the project.

Corresponding author

Correspondence to Yves Moreau.

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The authors declare no competing financial interests.

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Supplementary Figures 1–9, Supplementary Tables 1–5 and Supplementary Notes 1 and 2 (PDF 1456 kb)

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Sifrim, A., Popovic, D., Tranchevent, LC. et al. eXtasy: variant prioritization by genomic data fusion. Nat Methods 10, 1083–1084 (2013). https://doi.org/10.1038/nmeth.2656

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