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.
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.
||R version requirement
||Including probe-level variance
in model based clustering of gene expression data.
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