Make Plots
sai provides the plot command to generate a scatter plot of U statistic values versus Q statistic values for each genomic window.
To view the available options, we can run:
sai plot -h
This will show information for each argument:
| Argument | Description |
|---|---|
| -h, --help | show this help message and exit |
| --u-file | Path to the U score/outlier file. |
| --q-file | Path to the Q score/outlier file. |
| --output | Path to save the output plot file. The format depends on the file extension (e.g., .png, .pdf). |
| --xlabel | Label for the X-axis. Default: Q Statistic. |
| --ylabel | Label for the Y-axis. Default: U Statistic. |
| --title | Title of the plot. Default: Scatter Plot of U vs Q. |
| --figsize-x | Width of the figure (in inches). Default: 6. |
| --figsize-y | Height of the figure (in inches). Default: 6. |
| --dpi | Resolution of the saved plot. Default: 300. |
| --alpha | Transparency level of scatter points. Default: 0.6. |
| --marker-size | Size of the scatter plot markers. See matplotlib.pyplot.scatter. Default: 20. |
| --marker-color | Color of the markers. See matplotlib.pyplot.scatter. Default: blue. |
| --marker-style | Shape of the markers. See matplotlib.pyplot.scatter. Default: o. |
Input files
Two input files are required: one containing U statistic values and one containing Q statistic values. These files can be generated by either the score or outlier command.
Output files
The output file is a scatter plot showing U versus Q statistic values for each genomic window.
Examples
To plot the U statistics versus Q95 statistic values for genomic windows for detecting introgressed variants from both Neanderthals and Denisovans, we can run the following:
sai plot --u-file examples/results/1KG.nea_den.chr9.example.both.U.scores.tsv \
--q-file examples/results/1KG.nea_den.chr9.example.both.Q95.scores.tsv \
--output examples/results/1KG.nea_den.chr9.example.both.U.vs.Q95.png
A file ending with .intersection.tsv (e.g., 1KG.nea_den.chr9.example.both.U.vs.Q95.intersection.tsv) is also generated to record the data points used in the plot.
The resulting plot is shown below:
