cluster_quality.py – compute the quality of a cluster¶
Description:
The input is a distance matrix (i.e. resulting file from beta_diversity.py).
Usage: cluster_quality.py [options]
Input Arguments:
Note
[REQUIRED]
- -i, --input_path
- Input distance matrix file
- -m, --map
- Mapping file
- -c, --category
- Column of mapping file delimiting clusters
[OPTIONAL]
- -o, --output_path
- Output path, prints to stdout if omitted
- -s, --short
- Print only the ratio of mean dissimilarities between/within clusters instead of more detailed output
- --metric
- Choice of quality metric to apply. Currently only one option exists, the ratio of mean(distances between samples from different clusters) to mean(distances between samples from the same cluster) Default: ratio
Output:
The output is either a single number (with -s), or a more detailed output of the similarity between and within clusters.
cluster quality based on the treatment category:
to compute the quality of clusters, and print to stdout, use the following idiom:
cluster_quality.py -i weighted_unifrac_otu_table.txt -m Fasting_Map.txt -c Treatment
cluster quality based on the DOB category:
to compute the quality of clusters, and print to stdout, use the following idiom:
cluster_quality.py -i weighted_unifrac_otu_table.txt -m Fasting_Map.txt -c DOB