Association mapping from sequencing reads using k-mers

  1. Atif Rahman  Is a corresponding author
  2. Ingileif Hallgrímsdóttir
  3. Michael Eisen
  4. Lior Pachter  Is a corresponding author
  1. University of California, Berkeley, United States
  2. Howard Hughes Medical Institute, University of California, Berkeley, United States

Abstract

Genome wide association studies (GWAS) rely on microarrays, or more recently mapping of sequencing reads, to genotype individuals. The reliance on prior sequencing of a reference genome limits the scope of association studies, and also precludes mapping associations outside of the reference. We present an alignment free method for association studies of categorical phenotypes based on counting k-mers in whole-genome sequencing reads, testing for associations directly between k-mers and the trait of interest, and local assembly of the statistically significant k-mers to identify sequence differences. An analysis of the 1000 genomes data show that sequences identified by our method largely agree with results obtained using the standard approach. However, unlike standard GWAS, our method identifies associations with structural variations and sites not present in the reference genome. We also demonstrate that population stratification can be inferred from k-mers. Finally, application to an E.coli dataset on ampicillin resistance validates the approach.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 5.

The following previously published data sets were used

Article and author information

Author details

  1. Atif Rahman

    Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, United States
    For correspondence
    atif@cse.buet.ac.bd
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1805-3971
  2. Ingileif Hallgrímsdóttir

    Department of Statistics, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Michael Eisen

    Department of Molecular and Cell Biology, Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7528-738X
  4. Lior Pachter

    Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, United States
    For correspondence
    lpachter@caltech.edu
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (NIH R21 HG006583)

  • Atif Rahman
  • Ingileif Hallgrímsdóttir
  • Michael Eisen
  • Lior Pachter

Fulbright Science and Technology Fellowship (15093630)

  • Atif Rahman

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Jonathan Flint, University of California, Los Angeles, United States

Version history

  1. Received: October 18, 2017
  2. Accepted: June 8, 2018
  3. Accepted Manuscript published: June 13, 2018 (version 1)
  4. Version of Record published: July 13, 2018 (version 2)

Copyright

© 2018, Rahman et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Atif Rahman
  2. Ingileif Hallgrímsdóttir
  3. Michael Eisen
  4. Lior Pachter
(2018)
Association mapping from sequencing reads using k-mers
eLife 7:e32920.
https://doi.org/10.7554/eLife.32920

Further reading

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    In most of the world, the mammography screening programmes were paused at the start of the pandemic, whilst mammography screening continued in Denmark. We examined the mammography screening participation during the COVID-19 pandemic in Denmark.

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    The study comprised 1,828,791 invitations among 847,766 women. Before the pandemic, 80.2% of invitations resulted in participation in mammography screening within 90 d, 82.7% within 180 d, and 83.1% within 365 d. At the start of the pandemic, the participation in screening within 90 d was reduced to 69.9% for those invited in pre-lockdown and to 76.5% for those invited in first lockdown. Extending the length of follow-up time to 365 d only a minor overall reduction was observed (PR = 0.94; 95% CI: 0.93–0.95 in pre-lockdown and PR = 0.97; 95% CI: 0.96–0.97 in first lockdown). A lower participation was, however, seen among immigrants and among women with a low income.

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    The short-term participation in mammography screening was reduced at the start of the pandemic, whilst only a minor reduction in the overall participation was observed with longer follow-up time, indicating that women postponed screening. Some groups of women, nonetheless, had a lower participation, indicating that the social inequity in screening participation was exacerbated during the pandemic.

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    The study was funded by the Danish Cancer Society Scientific Committee (grant number R321-A17417) and the Danish regions.

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