A Pie Chart is a type of graph that displays data in a circular graph. It gives you a snapshot of how a group is broken down into smaller pieces. Because the pieces of a Pie chart are proportional to the fraction of the whole in each category. In order to make a Pie chart, you must have a list of categorical variables (descriptions of your categories, like ‘cell type’) as well as numeric variables (e.g.,  cell numbers). In Partek Flow, the default numeric variable is the cell numbers.  Therefore, the Pie chart indicates the fraction of the whole cell numbers in each category.

To make a Pie chart, open a new Data Viewer session in Flow.

Figure 1. New Data Viewer session in Flow

The chart title is based on the genomic feature (e.g. gene or transcript) that the plot was invoked on. The y-axis is scaled automatically, based on the range of the data, and the units correspond to the input units of the parent Feature list node, i.e. if the data were normalized using transcripts per million (TPM), the y-axis will be in TPM-normalised counts. Dots represent samples. Hovering the cursor over a sample invokes a popup balloon message shows sample ID and the respective expression value. The legend is in the upper right corner and is based on the data attribute specified under the Color by option (on the left).

Plot controls are in the panel on the left. The <Previous and Next> buttons enable you to switch between genomic features as they appear in the parent Feature list. The Group by option defines the grouping on the x-axis, with the drop-down list containing the data attributes as present in the Data tab. As previously mentioned, the dot colors are controlled by the Color by option. If you want to change a color, select the Customize colors hyperlink. The resulting dialog (Figure 2) will enable you to replace an existing color by a color of your choice (click on the arrow head to invoke the color mixer) or add more colors (Add color).

Figure 2. Customize colors dialog (default appearance). General tab (palette) is used for sample coloring and general sample attribute-based coloring in the chromosome view, hierarchical clustering, and general charts and graphs. Two-color numeric tab (palette) is used to color by numeric sample attribute in the hierarchical clustering, principal components analysis, and dot plot views. The Save button saves your color preferences

The Connect by option is particularly useful for dependent study designs, where you can highlight the samples based on the same biological source by the connecting lines. The example on Figure 3 depicts results of a study where each RNA sample was processed by both RNA-seq and gene array; the lines connect the same samples. Finally, the Show box plot turns on (or off) per-group box-and-whiskers (for each level of the Group by attribute).

Figure 3. Dot plot with samples connected by a sample ID, to highlight the dependent study design

Once you are pleased with the appearance of the dot plot, push Save image button to save it to the local machine. The resulting dialog (Figure 4) controls the resolution of the image file. The image will be saved in svg format, and the default file name is Dot plot.svg

Figure 4. Save image dialog (default settings)

Use the Group order section of the control panel to change the order of the groups on the x-axis. Simply drag and drop a group label to a new position.

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