pumaclust: R package for gene expression clustering

pumaclust is an R package that clusters gene expression by inluding probe-level measurement error into consideration. It is a part of PUMA project.

Why is pumaclust different from other clustering methods?

Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the exploration of unknown gene functions. Due to the complicated multi-step microarray experiments, the resulting gene expression data are very noisy. Many heuristic and model-based clustering approaches have been developed to cluster this noisy data. However, few of them include consideration of probe-level measurement error which provides rich information about technical variability. We augment a standard model-based clustering method to incorporate probe-level measurement error. Using probe-level measurements from a recently developed Affymetrix probe-level model, multi-mgMOS, we include the probe-level measurement error directly into the standard Gaussian mixture model. The performance of model-based clustering of gene expression data is improved by including probe-level measurement error and more biologically reasonable clustering results are obtained. The probe-level measurement error are calculated from the R package mmgmos.

Download

pumaclust is free software; you can redistribute if and/or modify it under the terms of the GNU General Public License. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY. We do appreciate your citation of our publications or website.

A copy of user guide can be downloaded here. It is also included in the distribution.

Version	Linux add-on package	Windows add-on package	R version requirement	Description
1.1.0	pumaclust_1.1.0.tar.gz	pumaclust_1.1.0.zip	2.3.x	Including probe-level variance in model based clustering of gene expression data.

FAQ and bug report

1. What is the requirement of the installation of pumaclust?

In order to install pumaclust, you need to have R 2.3.x and BioConductor 1.8 installed. For the installation of R and BioConductor please refer to R project and BioConductor.org respectively.

2. How to install pumaclust?

Download the add-on package from the links above and save it to your local disk. For Linux users, at the directory where it is saved type

>R CMD INSTALL pumaclust_x.x.x.tar.gz

to install it. For Windows users, use 'Install package(s) from local zip files ...' item in 'packages' menu to install.

3. What if I spot a fault in pumaclust?

We are keen for feedback on pumaclust. If you experience a problem or bug, please report it via mailto:liux@cs.man.ac.uk. Any suggestion and comment are welcome.

Back to PUMA project