Brief Communication

GIGGLE: a search engine for large-scale integrated genome analysis

  • Nature Methods volume 15, pages 123126 (2018)
  • doi:10.1038/nmeth.4556
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Abstract

GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.

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Acknowledgements

We are grateful to the anonymous reviewers for their suggestions and comments. This research was funded by US National Institutes of Health awards to R.M.L. (K99HG009532) and A.R.Q. (R01HG006693, R01GM124355, U24CA209999).

Author information

Affiliations

  1. Department of Human Genetics, University of Utah, Salt Lake City, Utah, USA.

    • Ryan M Layer
    • , Brent S Pedersen
    • , Tonya DiSera
    • , Gabor T Marth
    •  & Aaron R Quinlan
  2. USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, Utah, USA.

    • Ryan M Layer
    • , Brent S Pedersen
    • , Tonya DiSera
    • , Gabor T Marth
    •  & Aaron R Quinlan
  3. Department of Oncological Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah, USA.

    • Jason Gertz
  4. Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA.

    • Aaron R Quinlan

Authors

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Contributions

R.M.L. conceived and designed the study, developed GIGGLE, and wrote the manuscript. B.S.P. developed the GIGGLE score and the PYTHON and GO APIs. T.D. developed the web interface. G.T.M. provided input in the development of the web interface. J.G. conceived and designed the ChIP-seq experiment. A.R.Q. conceived and designed the study and wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Ryan M Layer or Aaron R Quinlan.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–3 and Supplementary Tables 1–4

  2. 2.

    Life Sciences Reporting Summary

Zip files

  1. 1.

    Supplementary Data 1

    Data used to generate Figure 1.

  2. 2.

    Supplementary Data 2

    Data used to generate Figure 2.

  3. 3.

    Supplementary Software

    GIGGLE source code and experiment scripts.

Excel files

  1. 1.

    Supplementary Data 3

    Cell line, tissue, and trait names from Figure 1; accession numbers from Figures 1 and 2 and Supplementary Figure 2.