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With the probe intensities spreadsheet and the gene list open in the Analysis tab, follow these steps to filter the probe intensities spreadsheet. 

  • Select the probe intensities spreadsheet in the spreadsheet tree; here, it is Down_Syndrome-GE
  • Select Filter from the main task bar
  • Select Filter Columns
  • Select Filter Columns Base on a List... (Figure 1)

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Now we have a probe intensities spreadsheet containing only the probe intensity values for our 23 genes of interest (Figure 4).

 

 

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SubtitleTextFiltered probe intensities spreadsheet
AnchorNameFiltered probe intensities spreadsheet

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Violin Plot tab will open (Figure 5). This plot shows the intensity value ranges of the 23 genes (probe sets) for all samples as violin plots.

 

 

 

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SubtitleTextViewing violin plots for 23 genes
AnchorNameViolin Plots

 

 

  • Select View from the main taskbar
  • Select Toggle Properties

We can now see the plot properties panel to the left of the violin plot (Figure 6). 

 

 

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SubtitleTextThe violin plot can be configured using the plot properties panel
AnchorNameConfiguring Violin Plot

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SubtitleTextViewing average probe intensity values for two groups across 23 genes as box and whisker plots
AnchorNameBox and Whisker plot

 

To improve our view of the gene symbols, we can modify the X-axis legend. 

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SubtitleTextConfiguring the X-axis label
AnchorNameConfiguring x-axis

The gene symbol for each column should now be visilble (Figure 9). In cases where probe intensities for your genes of interest fall across a wide range, it may be helpful to normalize the probe intensity distributions of each gene. This is equivalent to what is done to display a heat map of probe intensity values. 

 

 

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SubtitleTextX-axis now labels with gene symbols for each gene
AnchorNameModified x-axis

 

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SubtitleTextViewing normalized box and whisker plots
AnchorNameNormalized box and whisker plots

 

 

 

Plots can also be split by categorical variables. We can use this to visualize differential expression of genes between Down syndrom and normal patients in different tissue types. 

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There should now be a sub-plot for each category, in this case there are four sub-plots, one for each tissue (Figure 13). There are no error bars for several plots because there are not enough samples in those categories. 

 

 

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SubtitleTextSplitting a plot by a categorical factor, Tissue, and grouping by another categorical variable, Type
AnchorNameSplitting plots

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