Category Genomics>Gene Expression Analysis/Profiling/Tools

Abstract EXPANDER (EXpression Analyzer and DisplayER) is a java-based tool for the analysis of gene expression data. It is capable of (1) preprocessing (2) visualizing (3) clustering (4) biclustering and (5) performing downstream analysis of clusters and biclusters such as functional enrichment and promoter analysis (i.e. analysis of gene groups for enrichment of transcription factor binding sites in their promoters).

EXPANDER incorporates several conventional gene expression analysis algorithms and custom ones that have been developed in the computational genomics group in Tel-Aviv University, and provides them with an easy-to-operate user interface.

Gene Expression Analysis Algorithms --


CLICK is a novel 'clustering algorithm' which is applicable to gene expression analysis as well as to other biological applications. No prior assumptions are made on the structure or the number of the clusters. The algorithm utilizes graph-theoretic and statistical techniques to identify tight groups of highly similar elements (kernels), which are likely to belong to the same true cluster.


SAMBA is a novel 'biclustering algorithm' for the identification of modules of genes that exhibit similar behavior under a subset of the examined biological conditions. SAMBA is an efficient way to discover statistically significant biclusters in large scale biological datasets, consisting of hundreds or thousands of diverse experiments. It extends the standard clustering approach by detecting subtle similarities between genes across subsets of the measured conditions and enabling genes to participate in several biclusters. Thus, it is more suitable for analyzing heterogeneous datasets.


TANGO tests whether the group of genes in each cluster is enriched for a particular function. The functions of the genes are determined according to Gene Ontology (GO) annotation files. Since the GO functions are highly related, TANGO performs hyper-geometric enrichment tests and corrects for multiple testing by bootstrapping and estimating the empirical p-value distribution for the evaluated sets.


PRIMA (PRomoter Integration in Microarray Analysis) is a program for finding transcription factors (TFs) whose binding sites are enriched in a given set of promoters. After identifying a group of co-regulated genes using clustering or biclustering, the promoters of the genes can be analyzed using PRIMA. By utilizing known models for binding sites (BSs) of TFs, PRIMA identifies TFs who’s BSs are significantly over- represented in that set of promoters. Such TFs are candidate regulators of the corresponding set of genes.

Highlights of features/capabilities of the Expander 4.0 software release --

1) Ability to load and analyze data in .cel (cell intensity) files format.

2) Missing value estimation using the KNN (K-Nearest Neighbors) algorithm.

3) T-test statistics.

4) Condition merge utility (calculating an average profile from a set of condition profiles).

5) Ability to run SAMBA and CLICK on large datasets.

6) Improved color scale range control.

7) Symbol auto-fill according to Entrez Ids.

8) Annotation files update.

9) Expanded promoter analysis range.

10) Ability to perform log2 operations on the data at the time of the analysis.

11) Support for the analysis of Chicken data (in addition to Human, Mouse, Rat, Fly, C. elegans, Arabidopsis and Yeast).

System Requirements

EXPANDER versions are available for Windows OS and for Linux/Unix OS and require the pre-installation of the Java Runtime Environment (JRE) 5.0 (or higher).


Manufacturer Web Site EXPANDER 4.0

Price Contact manufacturer.

G6G Abstract Number 20149

G6G Manufacturer Number 102304