Comparison of Biclustering Methods: A Systematic Comparison and Evaluation of Biclustering Methods for Gene Expression Data

Motivation: In recent years, there have been various efforts to overcome the limitations of standard clustering approaches for the analysis of gene expression data by grouping genes and samples simultaneously. The underlying concept, which is often referred to as biclustering, allows to identify sets of genes sharing compatible expression patterns across subsets of samples, and its usefulness has been demonstrated for different organisms and data sets. Several biclustering methods have been proposed in the literature; however, it is not clear how the different techniques compare to each other with respect to the biological relevance of the clusters as well as to other characteristics such as robustness and sensitivity to noise. Accordingly, no guidelines concerning the choice of the biclustering method are currently available.