Importing Agilent data

Chipster is capable of reading in generic microarray data. This data can be result files from the image analysis of scanned cDNA microarrays. For example, Agilent and ScanArray data are imported this way.

All files should be stored in a single folder that can then be imported to Chipster. Select File->Import files, and browse to the correct folder that contains the dataset. Select the files you want to import. You can select several files either by pressing down the Control (Ctrl) key or the Shift key.

In the next window you define whether your files should be imported directly or by using the Import tool. Typically you don't need to change anything, since the column Action lists all files as 'Use Import tool'. This means that you need to describe the datafile to the system once, and it loads all the other files in similarly by default. To get to define the file, click on OK.

The Import tool opens. First, you need to define the rows that are the header information. Click on the Mark header -button on the top, and paint the rows you want to mark as header. Next, click on the Mark title row -button, and click on the title row:

Clicking Next opens the second step of the Import tool, where you define the columns of your data file to be used in Chipster. You have to define the following columns:

You can also mark columns Annotation (ControlType). Using the Annotation column allows you to remove the control probes from your dataset during the normalization step (by setting the 'remove control probes' parameter to yes). Please note that if you remove the control probes, you cannot use the data anymore for gene set test.

To define the columns, select the meaning by clicking on the button on the top of the page, and then click on one of the columns (not the greyed header).

If you have dye-swap arrays in your experiment, you should import your data in two phases. First import the un-swapped data file labeling the columns as specified. Next, import the dye-swapped arrays by switching the sample and control column.

To conclude the import, click on the Finish-button. After the data has been imported, it is displayed under datasets and in the workflow view:

Now the data has been successfully imported, and you should normalize it. You can also run some quality control checks on the raw data.