Genomics Suite Documentation

PGS Documentation

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  • For this tutorial, unzip the files to C:\Partek Training Data\Down_Syndrome_-GE or to a directory of your choosing. Be sure to create a directory or folder to hold the contents of the zip file
  • Copy or move the annotation files (HG-U133A.cdf, HG-U133A.na36.annot, HG-U133A.na36.annot.idx) to C:\Microarray Libraries. (Copying the annotation files to the default library location is done because newer annotation files that are released after the publication of this tutorial may cause the results to be different than what is shown in the published tutorial. If, however, you prefer to download the latest version, you may omit copying the HG-U133A files to C:\Microarray Libraries)
  • Start PGS and select Gene Expression from theWorkflowspanelon the right side of the tool bar in the PGS main window (Figure 1)

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Figure 1
Figure 1
Figure 1: Selecting the gene expression workflow

  • Select Import samples Samples under the Import section of the workflow
  • Select Import from Affymetrix CEL filesFiles and then click OK
  • Click Select the Browse button to select the C:\Partek Training Data\Down_Syndrome-GE folder. By default, all the files with a .CEL extension are selected(Figure 2)

 

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Figure 2
Figure 2
Figure 2: Selecting the folder and CEL files for the experiment

  • Select the Add File(s) > button to move all the .CEL files to the right panel. Twenty-five CEL files will be processed
  • Select the Next > ;button to open the Import Affymetrix CEL Files dialog is shown in (Figure 3)

 

  • Select Customize… to configure the import options (Figure 4) 

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The next step is to draw a histogram to examine the samples. Select Plot Sample Histogram in the QA/QC section of the Gene Expression workflowto generate the Histogram tab as shown in Figure 18.

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The histogram plots one line for each of the samples with the intensity of the probes graphed on the X-axis and the frequency of the probe intensity on the Y-axis. This allows you to view the distribution of the intensities to identify any outliers. In this dataset, all the samples follow the same distribution pattern indicating that there are no obvious outliers in the data. As demonstrated with the PCA plot, if you click on any of the lines in the histogram, the corresponding row will be highlighted in the spreadsheet 1 (Down_Syndrome-GE). [PF1] You can also change the way the histogram displays the data by clicking on the Plot Properties button. Explore these options on your own.

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