PDM

Partition Decoupling Method

The PDM package carries out the Partition Decoupling Method (PDM), an unsupervised machine-learning technique that consists of two iterated submethods: a spectral clustering step that finds the dominant clusters of samples, and a "scrubbing" step that removes this structure (by projecting the data onto the cluster centroids and taking the residuals) such that the next clustering iteration can articulate an independent set of clustering relationships. The method is fully described in:

• Rosemary Braun, Greg Leibon, Scott Pauls, and Daniel Rockmore. Partition Decoupling for Multi-Gene Analysis of Gene Expression Profiling Data. BMC Bioinformatics, 12:497 (2011).

R package

A complete R package is available and may be dounloaded here and installed from source:

• Complete source package:
  PDM_1.1.tar.gz
• Package vignette decribing the usage of the PDM package:
  PDM.pdf
• Package manual:
  PDM-manual.pdf

Citations

If you use the PDM package or source code, please cite:

• Rosemary Braun, Greg Leibon, Scott Pauls, and Daniel Rockmore. Partition Decoupling for Multi-Gene Analysis of Gene Expression Profiling Data. BMC Bioinformatics, 12:497 (2011).

Issues?

Please email Rosemary Braun at rosemary.braun_AT_GMAIL_DOT_COM if you have any questions, concerns, or feedback!