Differential co-expression framework to quantify goodness of biclusters and compare biclustering algorithms

In this paper we propose differential co-expression framework and a differential co-expression scoring function to objectively quantify quality or goodness of a bicluster of genes based on the observation that genes in a bicluster are co-expressed in the conditions belonged to the bicluster and not co-expressed in the other conditions. Furthermore, we propose a scoring function to stratify biclusters into three types of co-expression. We used the proposed scoring functions to understand the performance and behavior of the four well established biclustering algorithms on six real datasets from different domains by combining their output into one unified ranking.Differential co-expression framework is useful to provide quantitative and objective assessment of the goodness of biclusters of co-expressed genes and performance of biclustering algorithms in identifying co-expression biclusters. It also helps to combine the biclusters output by different algorithms into one unified ranking i.e. meta-biclustering.The inception of microarrays has facilitated quantification of expression of genes at genomic scale in large sets of conditions in time and cost effective manner resulting in a wealth of massive gene expression datasets. Appropriate analysis of these datasets lead to the understanding of the roles of various genes and pathways at genomic-scale.Significant portion of microarray data analysis is unsupervised in which the genes are grouped according to the similarity of their expression patterns among multiple conditions. It is based on the observation that the genes involved in similar biological regulatory pathways or functions exhibit similar expression patterns i.e. a cluster of genes may demonstrate a consistent co-expression pattern among most conditions. Several techniques such as agglomerative or divisive clustering algorithms [1-4] that partition the genes into mutually exclusive groups or hierarchies have been reported. On the other hand, unlike the above tra