GeneSpring GX is powerful visualization and analysis software, regarded as the gold standard in desktop expression analysis. By performing supervised and unsupervised clustering analysis, GeneSpring GX gives you a broad choice of sophisticated methods for uncovering the most abundant patterns in your gene expression data and understanding how those patterns are related. By providing advanced statistical tools, it enables differential expression analysis for prediction of clinical outcomes and characterization of novel expression patterns. GeneSpring GX provides intuitive graphical displays and visualization tools including 2D and 3D scatter plots, volcano plots, box plots, 2D dendrograms, chromosome maps, etc. To answer complex biological questions, scientists can perform pathway and functional analysis of differentially expressed genes using pathway diagrams (including GenMapp and KEGG) and GO ontology browser classification views.
GeneSpring GX allows you to drag-n’-drop data from Agilent, Affymetrix, GE Healthcare, and Illumina expression analysis systems. Expression data is normalized using global per-chip or per-gene normalization, as well as custom normalization to specified control samples. Gene and experiment trees, SOMs, k-means and QT clustering are available to perform supervised and unsupervised clustering analysis and understand how those clusters are related. To determine which genes are differentially expressed in individual samples or groups of samples, GeneSpring provides a host of advanced statistical tools including t-tests, one- and two-parameter ANOVA tests, one-way post-hoc tests, and class prediction tools. A variety of options is available for the multiple testing corrections. In addition, GeneSpring GX class prediction tools can identify genes capable of discriminating between one or more experimental parameters or sample phenotypes. Groups of genes identified by expression profiling can be further characterized by performing sequence searches for potential regulatory elements. Data can be also transferred into third-party applications such as BioConductor, SAS, MATLAB® and R algorithms.
I extensively used GeneSpring GX 7.3 to perform comprehensive analysis of the expression signals of 46000 transcripts for twelve patients with a hereditary muscle abnormality and matching controls collected using Illumina’s platform. The older version of GeneSpring GX did not have drag n' drop option for Illumina data downloading; it took me a day’s work and a call to the technical support to finally download the data. Despite the help from co-workers familiar with the software and the availability of several manuals, I called the technical support daily. The technical support staff was very helpful. GeneSpring GX 7.3 has a very complicated interface with a variety of hidden options and complicated data storage. Each project can have dozens of folders containing gene and sample trees – results of clustering analysis, lists of differentially expressed genes, results of statistical testing of expression differences between samples and sample groups, folders with pathway maps, folders with plots, etc, etc. The more comprehensive analysis you perform, the more data you accumulate and need to keep track of. But the possibilities are endless. The latest major release, GeneSpring GX 7.3.1, offers a lot of improvements including easier access to information about gene function, additional linkage algorithms, new plots, improved pathway analysis, and finally, a drag n' drop option for Illumina BeadStudio data format.
Based on my experience, GeneSpring GX 7.3 is still the gold standard for expression analysis. It provides the researcher with nearly endless options for all manipulations but requires time to and help of others to become familiar with the software.
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Yelena Bykhovskaya, PhD
Research Scientist I
Molecular Hematology Laboratory
Cedars-Sinai Medical Center
United States
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