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Controlling the false-positive rate in multilocus genome scans for selection.

Kevin R Thornton1, Jeffrey D Jensen

  • 1Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA. krthornt@uci.edu

Genetics
|November 18, 2006
PubMed
Summary

Ignoring locus ascertainment in genome scans can falsely suggest natural selection. A simple correction for this bias restores accurate false-positive rates, crucial for reliable population genetics studies.

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Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Genomics

Background:

  • Genome scans rapidly survey genetic variation to detect natural selection.
  • Identifying genomic regions under recent selection is key to understanding evolutionary processes.
  • Subsequent analysis of selected regions often involves parametric tests for selection and estimating selective sweep strength.

Purpose of the Study:

  • To demonstrate how ignoring locus ascertainment biases analyses of natural selection.
  • To introduce a correction method for ascertainment bias in population genetics.
  • To evaluate methods for detecting recent selective sweeps using genomic data.

Main Methods:

  • Simulations were used to model genetic variation and selection.
  • A correction for ascertainment bias was developed and applied.
  • Statistical tests were performed to assess the effectiveness of the correction.
  • Different summary statistics and region sizes were compared for detecting selective sweeps.

Main Results:

  • Failure to account for locus ascertainment leads to false positives for natural selection under neutrality.
  • The proposed correction effectively reduces false-positive rates to nominal levels.
  • Accurate accounting for both region ascertainment and population demography is essential for valid P-value distributions.
  • Measures of diversity and population differentiation are more powerful than site-frequency spectrum summaries for detecting sweeps.
  • Sequencing larger genomic regions (≥2.5 kbp) increases the power to detect recent selective sweeps.

Conclusions:

  • Ascertainment bias is a significant issue in detecting natural selection from genome scans.
  • A straightforward correction for ascertainment bias can improve the reliability of population genetics inferences.
  • Robust detection of recent selective sweeps requires careful consideration of ascertainment, demography, and data characteristics.