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  • To invoke the ANOVA dialog, select Detect Differentially Expressed Genes in the Analysis section of the Gene Expression workflow
  • In the Experimental Factor(s) panel, select Type, Tissue and Subject by pressing <Ctrl> and left clicking each factor
  • Use the Add Factor > button to move the selections to the ANOVA Factor(s) panel
  • To specify the interaction, select Type and Tissue by pressing <Ctrl> and left clicking each factor. Select the Add Interaction > button to add the Type * Tissue interaction to the ANOVA Factor(s) panel (Figure 1). Do NOT select OK or Apply. We will be adding contrasts to this ANOVA in an upcoming section of the tutorial. 

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  • Select Contrasts… to invoke the Configure dialog
  • Choose 6.Type from the Select Factor/Interaction drop-down list. The levels in this factor are listed on the Candidate Level(s) panel on the left side of the dialog
  • Left click to select Down Syndrome from the Candidate Level(s) panel and move it to the Group 1 panel (renamed Down Syndrome) by selecting Add Contrast Level > in the top half of the dialog. Label 1 will be changed to the subgroup name automatically, but you can also manually specify the label name 
  • Select Normal from the Candidate Level(s) panel and move it to the Group 2 panel (renamed Normal) 
  • The Add Contrast button can now be selected (Figure 2)

Numbered figure captions
SubtitleTextAdding a contrast of Down Syndrome and Normal samples
AnchorNameConfiguring ANOVA Contrasts

Because the data is log2 transformed, PGS will automatically detect this and will automatically select Yes in the Data is already log transformed? at the top right-hand corner. PGS will use the geometric mean of the samples in each group to calculate the fold change and mean ratio for the contrast between the Down syndrome and Normal samples.

  • Select Add Contrast to add the Down Syndrome vs. Normal contrast 
  • Select OK to apply the configuration
  • If successfully added, the Contrasts… button will now read Contrasts Included (Figure 3)

Numbered figure captions
SubtitleTextANOVA configuration with contrasts included
AnchorNameANOVA Configuration with Contrasts

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The result will be displayed in a child spreadsheet, ANOVA-3way (ANOVAResults). In the child result spreadsheet, each row represents a gene, and the columns represent the computation results for that gene (Figure 4). By default, the genes are sorted in ascending order by the p-value of the first categorical factor. In this tutorial,Type is the first categorical factor, which means the most highly significant differently expressed gene between Down syndrome and normal samples is at the top of the spreadsheet in row 1.

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  • View the sources of variation for each of the factors across the whole genome by clicking Plot Sources of Variation from the Analysis section of the Gene Expression workflow with the ANOVA result spreadsheet active
  • Sources of Variation tab will appear (Figure 5) with a bar chart showing the signal to noise ratio for each factor. Sources of variation can also be viewed as a pie chart showing sum or squares by selecting the Pie Chart (Sum of Squares) tab in the upper left-hand side of the Sources of Variation tab

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  • Right-click on a row header in the ANOVA spreadsheet (Figure 6)
  • Select ANOVA Interaction Plot from the options to generate an Interaction Plot tab for that individual gene

Numbered figure captions
SubtitleTextCalling an ANOVA Interaction Plot for a gene
AnchorNameCalling ANOVA Interaction Plot

Generate these plots for rows 3 (DSCR3) and 8 (CSTB). If the lines in this plot are not parallel, then there is a chance there is an interaction between Tissue and Type. DSCR3 is a good example of this (Figure 7). We can look at the p-values in column 9, p-value(Type * Tissue) to check if this apparent interaction is statistically significant. 

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  • Right click on the gene row header and select Dot Plot (Orig. Data) from the pop-up menu. This generates a Dot Plot tab for the selected gene (Figure 8)

Numbered figure captions
SubtitleTextDot Plot showing DSCR3 expression levels for each sample
AnchorNameDot Plot

In the plot, each dot is a sample of the original data. The Y-axis represents the log2 normalized intensity of the gene and the X-axis represents the different types of samples. The median expression of each group is different from each other in this example. The median of the Down syndrome samples is ~6.3, but the median of the normal samples is ~6.0. The line inside the Box & Whiskers represents the median of the samples in a group. Placing the mouse cursor over a Box & Whiskers plot will show its median and range. 

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  • Invoke the List Manager dialog by selecting Create Gene List in the Analysis section of the Gene Expression workflow
  • Ensure that the 1/ANOVA-3way (ANOVAResults) spreadsheet is selected as this is the spreadsheet we will be using to create our new gene list as shown (Figure 9)
  • Select the ANOVA Streamlined tab. In the Contrast: find genes that change between two categories panel, choose Down Syndrome vs. Normal and select Have Any Change from the Setting dropdown menu listThis will find genes that have a fold change different between the types of samples
  • In the Configuration for “Down Syndrome vs Normal” panel, check that Include size of the change is selected and enter 1.3 into Fold change >  and -1.3 in OR Fold change <
  • Select Include significance of the change, choose unadjusted p-value from the dropdown menu, and < 0.0005 for the cutoff. The number of genes that pass your cutoff criteria will be shown next to the # Pass field. In this example, 23 genes pass the criteria. 
  • Set Save the list as A, select Create, and then select Close to view the new gene list spreadsheet

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  • Select the 1/ANOVA-3way (ANOVAResults) spreadsheet in the Analysis tab. Thisis the spreadsheet we will be using to create the gene list
  • Select View > Volcano Plot from the PGS main menu (Figure 10)

Numbered figure captions
SubtitleTextGenerating a Volcano Plot from ANOVA results
AnchorNameGenerating Volcano Plot

  • Set X Axis (Fold-Change) to 12. Fold-Change(Down Syndrome vs. Normal), and the Y axis (p-value) to be 110. p-value(Down Syndrome vs. Normal)
  • Select OK to generate a Volcano Plot tab and for genes in the ANOVA spreadsheet (Figure 11)

Numbered figure captions
SubtitleTextVolcano plot generated from ANOVA spreadsheet
AnchorNameVolcano Plot

In the plot, each dot represents a gene. The X-axis represents the fold change of the contrast, and the Y-axis represents the range of p-values. The genes with increased expression in Down syndrome samples on the right side; genes with reduced expression in Down syndrome samples are on the left of the N/C line. The genes become more statistically significant with increasing Y-axis position. The genes that have larger and more significant changes between the Down syndrome and normal groups are on the upper right and upper left corner. 

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  • Select Rendering Properties ()
  • Choose the Axes tab
  • Check Select all points in a section to allow PGS to automatically select all the points in any given section
  • Select the Set Cutoff Lines button and configure the Set Cutoff Lines dialog as shown (Figure 12)

Numbered figure captions
SubtitleTextSetting cutoff lines for -1.3 to 1.3 fold changes and a p-value of 0.05
AnchorNameSet Cutoff Lines

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  • Right-click on the selected region in the plot and choose Create List to create a list including the genes from the section selected (Figure 13). Note that these p-values are uncorrected

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  • Specify a name for the gene list (example: volcano plot list) and write a brief description about the list. The description is shown when you right-click on the spreadsheet > Info > Comments. Here, I have named the list "volcano plot list" and described it as "Genes with >1.3 fold change and p-value <0.05" (Figure 14). 

 The list can be saved as a text file (File > Save As Text File) for use in reports or by downstream analysis software.

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