conditional_uncovered_probability.py – Calculate the conditional uncovered probability on each sample in an otu table.¶
Description:
This script calculates the conditional uncovered probability for each sample in an OTU table. It uses the methods introduced in Lladser, Gouet, and Reeder, “Extrapolation of Urn Models via Poissonization: Accurate Measurements of the Microbial Unknown” PLoS 2011.
Specifically, it computes a point estimate and a confidence interval using two different methods. Thus it can happen that the PE is actually outside of the CI.
We only provide the ability to generate 95% (alpha=0.95) CIs. The CIs are ULCL CIs; they provide an upper and lower bound, where the lower bound is conservative. The CIs are constructed using an upper-to-lower bound ratio of 10.
The CI method requires precomputed constants that depend on the lookahead. We only provide constants for r=3..25,30,40,50.
Usage: conditional_uncovered_probability.py [options]
Input Arguments:
Note
[OPTIONAL]
- -i, --input_path
- Input OTU table filepath. [default: None]
- -o, --output_path
- Output filepath to store the predictions. [default: None]
- -r, --look_ahead
- Number of unobserved, new colors necessary for prediction. [default: 25]
- -m, --metrics
- CUP metric(s) to use. A comma-separated list should be provided when multiple metrics are specified. [default: lladser_pe,lladser_ci]
- -s, --show_metrics
- Show the available CUP metrics and exit.
Output:
The resulting file(s) is a tab-delimited text file, where the columns correspond to estimates of the cond. uncovered probability and the rows correspond to samples. The output file is compatible with the alpha_diversity output files and thus could be tied into the rarefaction workflow.
Example Output:
PE | Lower Bound | Upper Bound | |
---|---|---|---|
PC.354 | 0.111 | 0.0245 | 0.245 |
PC.124 | 0.001 | 0.000564 | 0.00564 |
Default case:
To calculate the cond. uncovered probability with the default values, you can use the following command:
conditional_uncovered_probability.py -i otu_table.biom -o cup.txt
Change lookahead:
To change the accuracy of the prediction change the lookahead value. Larger values of r lead to more precise predictions, but might be unfeasable for small samples. For deeply sequenced samples, try increasing r to 50:
conditional_uncovered_probability.py -i otu_table.biom -o cup_r50.txt -r 50