How SCOUTS-violins works ======================== About SCOUTS-violins -------------------- SCOUTS-violins was designed as an exploratory interface through which users can visualize the results from a SCOUTS analysis. Note that some options in SCOUTS-violins may result in errors, depending on how you chose to use SCOUTS - e.g. you can't inspect non-outliers or OutR outliers if you did not select those rules when running SCOUTS. Page elements ------------- This section explains what every button and option of the SCOUTS-violins interface does. Main window *********** These are the elements of the main window: .. image:: _static/gui/scouts_violins_main_page_annotations.png :scale: 30% :alt: SCOUTS main window - annotated :align: center **1) Load raw data**: Select the same input file given to SCOUTS. **2) Load SCOUTS results**: Select the same output folder used to save SCOUTS results. **3) Select sample names**: Write sample names to plot, separated by semicolons (e.g. "control;patient;drug01"). **4) and 5) Populations to compare**: Select populations to compare on the violin plot. The population in the top selection box appears below the population in the bottom box. **6) Marker**: Select marker for which to compare populations. Markers are automatically loaded from the input file header. **7) Outlier type**: select whether to plot OutS or OutR outliers. **8) Legend**: Whether do display a legend in the figure. **9) Plot**: click here to plot the figure with the selected parameters. The figure opens in a separate window, and can be reloaded with new parameters by clicking again on this button. Plot window *********** This is the plot window: .. image:: _static/gui/scouts_violins_plot_page_annotations.png :scale: 20% :alt: SCOUTS samples window - numbered :align: center The plot window works like a regular `matplotlib figure window `_ - it can be stretched, edited and modified. You can also use the tool bar at the top (**1**) to zoom, move and export the plot in different formats.