Immune feature trends, clinical outcomes, and immunomodulators
We have three new modules this month.
First is the immune feature trends, which allows you to see how immune readouts vary across your groups, and how they relate to one another. The first visualization is a violin plot showing how various quantities vary over groups. For example you can see how the proliferation score varys over TCGA molecular subtypes. Next is the heatmap of correlations. With a dropdown menu, you can select the variable class, like ‘core expression signature’, and then select a response variable, such as ‘stemness score RNA’. The heatmap is going to show the correlation of the factors selected in the variable class (as rows) vs the response variable for each subtype (in columns). The really neat thing here is that when you click on a box in the heatmap, the underlying data is shown.
Second module is the clinical outcomes. This is where you can produce survival curves with a Kaplan-Meier plot. In the case of continuous variables like ‘leukocyte fraction’, you can bin it into a selectable number of bins with the ‘value range divisions’ slider bar. Below that visualization is the concordance index. Here, you can explore which variables are associated with improved or diminished survival within your sample groups. Select a variable class, and you will get a heatmap, with one row for each variable in that class. For a given variable (row) and sample group (column) red denotes decreased survival, and blue increased survival as the variable is increased.
Last we have the immunomodulators module where you can visualize the expression of immunomodulatory genes within selected groups. By clicking on a violin plot, you can see the distribution of values for a given group of samples.