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Published on: February 15, 2017
Natural similarity measures between position frequency matrices with an application to clustering
Utz J Pape1, Sven Rahmann, Martin Vingron
1Computational Biology, Max Planck Institute f. Molecular Genetics, Ihnestr. 73, 14195 Berlin, Germany. utz.pape@molgen.mpg.de
Bioinformatics (Oxford, England)
|January 5, 2008
Summary
We developed a new method to measure similarity between transcription factor binding site models (PFMs) using asymptotic covariance. This approach effectively clusters PFMs and identifies distinct groups of transcription factors.
Area of Science:
- Computational Biology
- Bioinformatics
- Genomics
Background:
- Transcription factors (TFs) regulate gene expression by binding to DNA.
- Position frequency matrices (PFMs) represent TF binding sites.
- Comparing PFMs is crucial for discovering novel binding sites and avoiding redundancy.
Purpose of the Study:
- To propose a novel similarity measure for position frequency matrices (PFMs).
- To introduce a clustering method for Jaspar PFMs based on the proposed similarity.
- To provide a computational tool for PFM similarity and clustering.
Main Methods:
- Developed a similarity measure based on asymptotic covariance of PFM hits across both DNA strands.
- Introduced a clustering algorithm utilizing this asymptotic covariance measure.
- Efficiently computed asymptotic covariance using 2D convolution of score distributions.
Main Results:
- The asymptotic covariance method demonstrated strong correlation with simulated data.
- Outperformed three alternative PFM comparison methods in accuracy.
- Successfully clustered Jaspar PFMs into distinct groups, assigning a representative PFM to each class.
- PFMs with low similarity were automatically retained as singletons.
Conclusions:
- The proposed asymptotic covariance measure offers a robust and efficient way to assess PFM similarity.
- The clustering approach effectively groups related transcription factors.
- The developed methods and tools facilitate PFM analysis and discovery.
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