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Related Experiment Videos

Combining evidence using p-values: application to sequence homology searches

T L Bailey1, M Gribskov

  • 1San Diego Supercomputer Center, CA 92186-9784, USA.

Bioinformatics (Oxford, England)
|April 1, 1998
PubMed
Summary

This study introduces a new method for combining evidence from multiple sequence motifs to detect matches in biological sequences. The QFAST algorithm provides a statistically sound way to calculate combined p-values for improved sequence homology searches.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Statistical Genetics

Background:

  • Independent measures of sequence membership are common in bioinformatics.
  • Estimating the likelihood of sequence belonging to a class requires combining evidence.
  • Macromolecular sequence analysis often involves matching to multiple patterns (motifs).

Purpose of the Study:

  • To develop a statistically valid method for combining independent evidence sources.
  • To create a method that yields a single p-value for combined evidence.
  • To apply this method to detect simultaneous matches to multiple patterns in sequence homology searches.

Main Methods:

  • Expressing each piece of evidence as a p-value.
  • Using the product of independent p-values as a measure of evidence.

Related Experiment Videos

  • Deriving a formula and algorithm (QFAST) for the distribution of the product of p-values.

    • Main Results:

    • The QFAST algorithm calculates the statistical distribution of the product of n independent p-values.
    • Sorting sequences by the combined p-value effectively integrates information from multiple motifs.
    • This approach leads to highly accurate and sensitive sequence homology searches.

    Conclusions:

    • The QFAST method offers an intuitive and statistically sound approach to combining evidence in sequence analysis.
    • This method enhances the accuracy and sensitivity of detecting biological sequence families.
    • The approach is valuable for analyzing macromolecular sequences against multiple motifs.