PROPA: Probabilistic Pathway Annotation
- Bayesian Models and Analysis -

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Example 1:

This is an example concerning the pathway annotation for the ER status (+/-) of breast tumors presented in the 2010 Shen and West paper. The original gene expression data include 153 tumor samples. A simple regression analysis (with tumor ER status as independent variable) using BFRM generated an estimate of the probability of association with ER status for each of the 8764 unique genes. Then using the association probability data, PROPA computed the upper and lower bounds of the marginal likelihood of association between each of the 956 pathway gene sets (originally from MSigDB C2 collection) and tumor ER status.

Step 1: Estimation of association probabilities with BFRM
This is a data preparation step for the pathway annotation analysis with PROPA. For a PROPA trial purpose only, please skip this step.

Step 2: Pathway annotation with PROPA
The input files are:

  • parameters.txt
  • geneid.txt - Gene IDs of the 8764 genes.
  • p.txt - the data set containing association probabilities for 8764 unique genes.
  • geneset.txt - 956 reference gene sets. Each line is one gene set composed of unique Gene IDs of member genes.

Running PROPA from a command window: ./propa parameters.txt
The output file is result.txt.

Step 3: Presentation of pathway annotation results
The additional required information for analysis result report is saved in the following files:

  • p_sign.txt - association directions for the 8764 genes (1 for positively / -1 for negatively / 0 for not associated with ER status).
  • geneset_name.txt - names of the 956 gene sets.
  • geneset_sym.txt - 956 gene sets listed with gene symbols.

User can develop her/his own program to present the results. File dispresult.m is an example written in MATLAB, showing the top 30 pathway gene sets identified by PROPA.

All the files required for this example are archived in

PROPA developed by: Haige Shen, Quanli Wang & Mike West

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