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Related Experiment Videos

SCANMS: adjusting for multiple comparisons in sliding window neutrality tests.

David H Ardell1

  • 1Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Box 596, SE-751 24 Uppsala, Sweden.

Bioinformatics (Oxford, England)
|April 3, 2004
PubMed
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A new Perl utility, SCANMS, aids in analyzing genetic data by simulating sliding window analyses. It helps determine the significance of Tajima

Area of Science:

  • Population Genetics
  • Bioinformatics

Background:

  • Sliding window analysis is crucial for detecting selection in genomic data.
  • Accurate significance testing in sliding window analyses requires accounting for multiple comparisons.

Purpose of the Study:

  • To develop a computational tool for robust sliding window analysis of genetic data.
  • To facilitate the calculation of significance values and cutoffs in population genetics studies.

Main Methods:

  • Developed SCANMS, a Perl utility for analyzing parametric bootstrap data.
  • Simulated sliding window analyses of Tajima's D and Fu and Li's D(*) or F(*) statistics.
  • Generated empirical joint distributions of window minima and maxima from simulated data.

Main Results:

Related Experiment Videos

  • SCANMS simulates sliding window analyses on bootstrap replicates.
  • The tool generates empirical distributions of window statistics.
  • These distributions enable accurate significance testing for real genetic data.

Conclusions:

  • SCANMS provides a method to calculate achieved significance values and cutoffs.
  • The utility accounts for multiple comparisons inherent in sliding window analyses.
  • SCANMS enhances the reliability of detecting selection in population genetics.