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Under construction


The CressExpress ( provides a simple ReST-style web service you can use to download expression data in spreadsheet-friendly formats suitable for visualization in programs like TableView.

This tutorial demonstrates using TableView to view data from the CressExpression expression data web service.

Getting Started

Download and run TableView

To download and run TableView, click here.

If you have not already run TableView, it will download and install on your computer.

How it works: When you click the Image, your browser will download a JNLP (Java Web Start) file. The browser will read the file, which tells your browser where to obtain the compiled code for the TableView program. It then will download the code and try to run it. You may then see a new window that looks something like the figure below.

To continue loading the software, you must click Allow.

Load data

Open CressExpress Web services URL in TableView console

When TableView starts, the TableView table console appears on your desktop.

TableView Console

Choose File > Load Table

  • Enter the Web service URL :,249679_at&version=2_0&desc=1

This URL will retrieve data release 3.0 expression values for ATH1 probe sets 249678_at and 249679_at, which have the same target gene: AT5G35980.

Note that probe set 249678_at targets the five-prime region of the gene, and 249679_at targets the 3- prime region of the gene. (Skip ahead to the last figure if you would like to see what the gene looks like.) According to TAIR annotations, this gene generates two different transcript variants with alternative three prime ends. The probe set 249678_at can hybridize with both transcripts, but the probe set 249679_at can hybridize with the longer form, the variant with an extended 3-prime end relative to the other.

  • Click open

TableView will access the data from the CressExpress ReST Web service. Once it loads, you will see something like this:

Data from CressExpress expression data Web service loaded into TableView Load Table window

  • Click Load at bottom of the window. If you like, enter an easy-to-remember name for your table.

Once the data are loaded, the TableView console display your table data under the Tables icon. In this case, I loaded the table as AT5G35980 probe sets.

View data

Click table icon to view spreadsheet of data

Once the data are loaded into TableView, the new table will appear in the TableView Console window.

Note the many kinds of plots you can make using the data.

To start, view spreadsheet view of the data.

  • Click the table icon (far left)

A new window will appear on your desktop, showing the columns of data retrieved from the CressExpress expression data server. Each row represents expression data from one array from the CressExpress version 3.0 data release.

Click the column labeled exp to sort slides by experiment number. This will group all arrays from the same experiment, which will make selecting the corresponding points in the scatter plot (next section) easier.

Take a moment to scroll up and down through the list. Note how expression values for each of the two probe sets seem to match each other fairly closely. This is because the data are fairly well correlated; the two probe sets measure the same gene.

Also note how the expression values seem to range from 9 to 11. This is because the data have been processed using the RMA algorithm, which performs probe-level normalization and log-transforms the result data. As a result, the data tend to be tightly and symmetrically distributed around a mean. 

The KS value is a quality control statistic. For more information, see the CressExpress paper.

Spreadsheet view of loaded data

Create scatter plot showing relationships between the two probe sets

Go back to the TableView console.

  • Select your table under the Tables heading
  • Click the scatterplot icon.

A new window will appear.

  • Choose the two probe sets for the x and y axis
  • Click plot


Explore outliers

Note how the plot exhibits a high correlation between expression values from the two probe sets.

However, some of the points seem to deviate from central regression line. That is, there are some outlier arrays.

to be continued

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