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Haplotype Allele Frequency (HAF) Score: Predicting Carriers of Ongoing Selective Sweeps Without Knowledge of the Adaptive Allele

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Research in Computational Molecular Biology (RECOMB 2015)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9029))

Abstract

Methods for detecting the genomic signatures of natural selection are heavily studied, and have been successful in identifying many selective sweeps. For the vast majority of these sweeps the adaptive allele remains unknown, making it difficult to distinguish carriers of the sweep from non-carriers. Because carriers of ongoing selective sweeps are likely to contain a future most recent common ancestor, identifying them may prove useful in predicting the evolutionary trajectory– for example, in contexts involving drug-resistant pathogen strains or cancer subclones. The main contribution of this paper is the development and analysis of a new statistic, the Haplotype Allele Frequency (HAF) score, assigned to individual haplotypes in a sample. The HAF score naturally captures many of the properties shared by haplotypes carrying an adaptive allele. We provide a theoretical model for the behavior of the HAF score under different evolutionary scenarios, and validate the interpretation of the statistic with simulated data. We develop an algorithm (\(\text {PreCIOSS}\): Predicting Carriers of Ongoing Selective Sweeps) to identify carriers of the adaptive allele in selective sweeps, and we demonstrate its power on simulations of both hard and soft selective sweeps, as well as on data from well-known sweeps in human populations.

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Author information

Authors and Affiliations

  1. Bioinformatics Graduate Program, University of California, San Diego, La Jolla, CA, USA

    Roy Ronen

  2. Department of Mathematics, University of California, San Diego, La Jolla, CA, USA

    Glenn Tesler

  3. Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, USA

    Ali Akbari

  4. Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA

    Shay Zakov & Vineet Bafna

  5. Department of Biology, Stanford University, Stanford, CA, USA

    Noah A. Rosenberg

Authors
  1. Roy Ronen
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  2. Glenn Tesler
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  3. Ali Akbari
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  4. Shay Zakov
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  5. Noah A. Rosenberg
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  6. Vineet Bafna
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Corresponding author

Correspondence to Vineet Bafna .

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Editors and Affiliations

  1. National Center of Biotechnology Information, Bethesda, Maryland, USA

    Teresa M. Przytycka

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© 2015 Springer International Publishing Switzerland

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Ronen, R., Tesler, G., Akbari, A., Zakov, S., Rosenberg, N.A., Bafna, V. (2015). Haplotype Allele Frequency (HAF) Score: Predicting Carriers of Ongoing Selective Sweeps Without Knowledge of the Adaptive Allele. In: Przytycka, T. (eds) Research in Computational Molecular Biology. RECOMB 2015. Lecture Notes in Computer Science(), vol 9029. Springer, Cham. https://doi.org/10.1007/978-3-319-16706-0_28

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  • DOI: https://doi.org/10.1007/978-3-319-16706-0_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16705-3

  • Online ISBN: 978-3-319-16706-0

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