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Short description


SelTag is one of the best-of-breed tools for analyzing gene expression data.

    SelTag allows users to:
  • Select genes by their expression levels or other parameters obtained in various experiments
  • Sort genes by their expression levels determined in various experiments
  • Visualize gene expression profiles using advanced graphical tools
  • Search for genes with expression profiles similar to one or more genes
  • Assess the correlation between expression profiles of two or more genes
  • Cluster gene expression data by the similarity of their gene expression profiles and experiments by the similarity of gene expression levels
  • Perform hierarchical clustering of genes or tissues and display the results as similarity trees
  • Analyze the correlation and covariance matrices of gene expression profiles using the principal component method and visualize the results obtained
  • Integrate with external databases to retrieve the data for analysis (for example, UniGene database)

Thus, using SelTag, researchers can analyze all genes and tissues or their marked groups, choose tissue-specific genes basing on integrated criteria, visualize expression data, identify the genes with a correlated expression in a given set of tissues, isolate disease-specific genes with particular characteristics, such as receptors or secreted proteins.

Trial version of the program is availiable to download here.

SelTag help [PDF].

SelTag demo [ppt].


SelTag screenshot