ArrayStar  v3.0                            

Expanded Capability for Gene Expression Analysis, Gene Characterization and RNA-Seq Applications


ArrayStar has established its reputation as an easy-to-learn gene expression analysis software package that offers many visualization and analytical tools that are easy to use. ArrayStar v3.0 offers several NEW Features that simplify the process of gene expression data analysis and expand the capability of ArrayStar. These Features include:

  • An optional application QSeq for RNA-Seq application analyses
  • Expanded Gene Characterization tables
  • Expanded clustering graphics
  • Additional Normalization algorithms to expand the data types analyzed
  • Networking capability

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    RNA-Seq is a quantitative method for detecting and measuring mRNA expression levels. Such procedures permit comparisons of expression levels between different samples. RNA-Seq allows the execution of gene expression experiments through the use of NextGen technology. The QSeq application of ArrayStar v3.0 easily permits quantization of gene expression levels along with a wide range of visualizations.


    Heat Map of an RNA-Seq application (Click on picture for larger image)

    ArrayStar 3 Heat Map



    Heat Maps illustrate expression levels of the genes across a number of experiments.
  • Genes can be selected within the Heat Map for additional analysis.
  • The Gene Tree to the left of the Heat Map reveals a sub-tree of genes. Clicking on branches reveals cluster information.
  • Gene Ontology information is easy to obtain by passing the cursor over any gene name or Heat Map location.
  • Selection of genes or gene clusters in the Heat Map is shown in the expression level histogram in gray and illustrates relative expression levels.
  • Heat Map details can be found in this section

    • Gene Ontology

    ArrayStar v3.0 software enables researchers to perform a wider range of analyses on their data because of the expanded Gene Characterization features built into the software. The information pane on the right side of the image allows users to control the content shown in the view and to easily navigate to the ontology area of interest. The left side includes an association tree along with numerous statistical comparisons useful in determining the relative importance of the selected genes in specific processes. The image below shows a typical table and graph for a group of selected genes.

    Click here for more information about the ArrayStar 3.0 Gene Ontology capabilities.

    Gene Ontology Image (Click on picture for larger image)

    ArrayStar 3 Gene Ontology




    Other Visualization Features Included in ArrayStar v3.0


    Visualizations to assist in Gene Expression level analysis


    For analysis across a series of experiments, such as a time series or a related set of conditions, two powerful clustering algorithms are available in ArrayStar: Hierarchical Clustering and k-Means Clustering.

    The Hierarchical Clustering method groups data points by clustering them one-by-one into ever-growing groups. After grouping all of the data points, the resulting clusters are displayed in the Heat Map. Details on Heat Maps are below.

    The k-Means Clustering method differs from the Heat Map method since it groups data points by partitioning them into a fixed number of arbitrary groups and then repeatedly refining the groups. The Line Graph Thumbnail view, shown below, is best used to display the k-Means Clustering.  Click here for more information on k-Means Clustering.

    Expression Level Changes – Line Graphs and Thumbnail Graphs


    Line Graphs
    ArrayStar allows users to easily visualize the expression level changes seen in individual genes over the course of the experiment through the use of Line Graphs. Any gene can be highlighted by passing the cursor over it to generate the graphical representation of its expression. Analytical Features of this include:

  • Selection of desired gene reveals ontology information
  • View comparisons of different gene expression levels
    • Click here for additional information on Line Graph diagram.

    Line Graph (Click on picture for larger image)

    Expression level of selected genes over different experiments



    Thumbnail Line Graph


    ArrayStar’s Line Graph Thumbnails view displays a series of Line Graphs generated from a clustering. Each individual Line Graph shows a visualization of the data contained within one cluster.

    Expression levels are plotted vertically along the Y-axis, while the X-axis position for each point is determined by the experiment to which it belongs. Mouse-over a vertical gridline to view the experiment name.

    Click here for additional information on the Thumbnail Line Graph diagram.

    Thumbnail Line Graphs (Click on picture for larger image)

    Expression level from multiple clusters


    Data Analysis

    ArrayStar provides a wide range of statistical analysis tools and techniques that can be used to assist researchers in their gene selection studies. In addition, its filtering capabilities permit users to quickly examine and re-examine data based on different experimental assumptions and beliefs. Additional details can be obtained by clicking here.


    Scatter Plot

    ArrayStar software enables researchers to perform a wide range of analyses on their data. Multi-functional scatter plots can be generated that allow the user to easily select groups of genes for analysis. The image shown depicts a group of selected genes (white) that have been selected from the overall experiment viewed on a scatter plot.

    Scatter Plot Images (Click on picture for larger image)

    Scatter plot showing selected genes (white)



    Gene Table

    The Gene Table view contains detailed information for every gene in your project, including both the expression data (e.g. signal intensities and fold change values) as well as any annotations that are available from imported sources, such as the gene name(s) and gene ontology. Some annotations have special features, allowing you to hover over a term for more information, or click on a hot link to view detailed information online. Any gene subsets being investigated are indicated in the Gene Table, allowing you convenient access to key tabular information for the genes being visualized by other tools in the package.


    Gene Table (Click on picture for larger image)

    Gene table showing range of analytical parameters