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Statistics and Sensor Analytics

BEPro3 - Bayesian Estimator of Protein-Protein Association Probabilities

The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a data analysis application for analyzing multiple-bait, multiple-replicate, pull-down assay experiments. The software was developed for use with bait-prey pull-down assay experimental data by the Statistics Group and the Genomes to Life Program at Pacific Northwest National Laboratory.

BEPro3 takes, as input, a prey-by-bait association matrix (the output of protein pull-down analysis) where elements of the matrix represent some score of association between the bait and prey, which could be number of peptide identifications, protein abundance, or any other score that estimates the presence/absence of a relationship between the bait and prey. A two-part algorithm is applied to the matrix to make inferences about the associative properties of the bait and prey proteins.

First, using a binomial model and locally calculated prior probabilites of false positive and true positive rates, BEPro3 characterizes each prey protein as either Specific or Non-Specific based on an omnibus likelihood ratio test (LRT). A Bayesian analysis follows and is used to calculate posterior probabilites of protein-protein association. The algorithm is described in the following paper:

The second portion of the algorithm uses globally calculated priors to make a second set of posterior probability estimates. This is based on work by Gilchrist, Salter and Wagner:

  • Gilchrist, MA, Salter, LA and Wagner, A. "A statistical framework for combining and interpreting proteomic datasets." Bioinformatics. Vol 20, no. 5, pages 689-700. January 2004.
Protein network diagram

The above image is an example of a protein network diagram. Systems biologists may be able to use BEPro3 to uncover the protein-protein interactions that form these networks faster and more efficiently.

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