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If there are multiple design models and multiple distribution types included in the calculation, the fraction of genes using each model and type will be displayed as pie charts in the task result (Figure 9). Image Removed
Figure 9:
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SubtitleText | Pie charts of proportion of genes using each model and distribution in gene-specific analysis calculation |
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AnchorName | Gene proportion |
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Feature list with p-value and fold change generated from the best model selected is displayed in a table with other statistical information (Figure 10). Image Removed
Figure 10:
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SubtitleText | Feature list on |
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the gene-specific analysis result. Clicking on |
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the column header sorts the table. Panel on the left filters the table | AnchorName | Feature list |
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The following information is included in the table by default:
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By clicking on Optional columns, you can retrieve more annotation if there are any more annotation information in the annotation model you specified for quantification, like genomic location, strand information etc.
On the right of each contrast header, there is volcano plot icon ( ). Select it to display the volcano plot on the chosen contrast (Figure 11). Image Removed
Figure 11:
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SubtitleText | Volcano plot in comparison A vs B. X-axis represents fold change (linear scale), Y-axis represents negative logged p-value (unadjusted), each dot is a feature. |
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The horizontal line represents p-value of 0.05, two vertical lines represent fold change of -2 and 2. Lower left corner displays number of features passing the fold-change and p-value criteria | AnchorName | Volcano plot |
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Feature list filter panel is on the left of the table (Figure 12). Click on the black triangle ( ) to collapse and expand the panel.
Select the check box of the field and specify the cutoff, and press Enter to apply. After the filter has been applied, the total number of included features will be updated on the top of the panel (Result).
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SubtitleText | Feature list filter panel |
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AnchorName | Feature list filter panel |
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The filtered result can be saved into a filtered data node by selecting the
Generate list button at the lower-left corner of the table (
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Download button at the lower-right corner of the table downloads the table as a text file to the local computer.
If lognormal with shrinkage method was selected for GSA, a shrinkage plot is generated in the report (Figure 13). The plot helps to determine the threshold of low expression features. X-axis shows the log2 value of average coverage. If there is an increase before a monotone decrease trend on the left side of the plot, you need to set a higher threshold on the low expression filter, detailed information on how to set the threshold can be found from GSA white paper.Figure 13:
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SubtitleText | Shrinkage plot |
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AnchorName | Shrinkage plot |
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Differential gene expression (ANOVA)
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