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SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation from New-Generation Sequencing Data

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  • Rasmus Nielsen
  • Thorfinn Korneliussen
  • Anders Albrechtsen
  • Yingrui Li
  • Jun Wang

Abstract

We present a statistical framework for estimation and application of sample allele frequency spectra from New-Generation Sequencing (NGS) data. In this method, we first estimate the allele frequency spectrum using maximum likelihood. In contrast to previous methods, the likelihood function is calculated using a dynamic programming algorithm and numerically optimized using analytical derivatives. We then use a Bayesian method for estimating the sample allele frequency in a single site, and show how the method can be used for genotype calling and SNP calling. We also show how the method can be extended to various other cases including cases with deviations from Hardy-Weinberg equilibrium. We evaluate the statistical properties of the methods using simulations and by application to a real data set.

Suggested Citation

  • Rasmus Nielsen & Thorfinn Korneliussen & Anders Albrechtsen & Yingrui Li & Jun Wang, 2012. "SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation from New-Generation Sequencing Data," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-10, July.
    • Handle: RePEc:plo:pone00:0037558
    DOI: 10.1371/journal.pone.0037558
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    Cited by:

    1. Zheng Xu, 2023. "Association Testing of a Group of Genetic Markers Based on Next-Generation Sequencing Data and Continuous Response Using a Linear Model Framework," Mathematics, MDPI, vol. 11(6), pages 1-32, March.
    2. Hirzi Luqman & Daniel Wegmann & Simone Fior & Alex Widmer, 2023. "Climate-induced range shifts drive adaptive response via spatio-temporal sieving of alleles," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

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