categorized_dist_scatterplot.py – makes a figure representing average distances between samples, broken down by categories. I call it a ‘categorized distance scatterplot’

Description:

makes a figure representing average distances between samples, broken down by categories. I call it a ‘categorized distance scatterplot’. See script usage for more details. The mapping file specifies the relavent data - if you have e.g. ‘N/A’ values or samples you don’t want included, first use filter_samples_from_otu_table.py to remove unwanted samples from the mapping file, and thus the analysis. Note that the resulting plot will include only samples in both the mapping file AND the distance matrix.

Usage: categorized_dist_scatterplot.py [options]

Input Arguments:

Note

[REQUIRED]

-m, --map

Mapping file

-d, --distance_matrix

Distance matrix

-p, --primary_state

Samples matching this state will be plotted. E.g.: AgeCategory:Child . See qiime’s filter_samples_from_otu_table.py for more syntax options

-a, --axis_category

This will form the horizontal axis of the figure, e.g.: AgeYears . Must be numbers

-o, --output_path

Output figure, filename extention determines format. E.g.: “fig1.png” or similar. A “fig1.txt” or similar will also be created with the data underlying the figure

[OPTIONAL]

-c, --colorby

Samples will first be separated by this column of the mapping file. They will be colored by this column of the mapping file, and all comparisons will be done only among samples with the same value in this column. e.g.: Country. You may omit -c, and the samples will not be separated

-s, --secondary_state

All samples matching the primary state will be compared to samples matcthing this secondary state. E.g.: AgeCategory:Adult

Output:

a figure and the text dat for that figure

Canonical Example:

Split samples by country. Within each country compare each child to all adults. Plot the average distance from that child to all adults, vs. the age of that child

python categorized_dist_scatterplot.py -m map.txt -d unifrac_distance.txt -c Country -p AgeCategory:Child -s AgeCategory:Adult -a AgeYears -o fig1.png

Example 2:

Same as above, but compares Child with all other categories (e.g.: NA, Infant, etc.)

python categorized_dist_scatterplot.py -m map.txt -d unifrac_distance.txt -c Country -p AgeCategory:Child -a AgeYears -o fig1.svg