Description:

enrich pvalues 1.0b2

A simple script to compare p-values between a test and comparison dataset at a
variety of p-value cutoffs. By plotting the enrichment score at a variety of
cutoffs, it is possible to pick the optimal cutoff for your data.
Version: 1.0-beta2


Contents

Algorithm
Installation

Requirements


Usage



Algorithm
For each p-value in the interval between max_pval (default: 0.05) and
min_pval (default: 1e-15), we test at intervals of 1 and 5 for each order of
magnitute, e.g. 0.05, 0.01, 0.005, 0.001, 5e-4, 1e-4, 5e-5, 1e-6, … 1e-15.
To test, we simply take all identities with a p-value less than the cutoff and
compare them to all identities in the comparison set with p-values below the
comp_set_pvalue. We simply ask what percentage or the test set are in the
comparison set. We then do exactly the same with the entire set of identities in
the comparison set that have a p-value greater than 0.98.
The identities are generally going to be gene or SNP names, but they can be
anything (e.g. coordinates) as long as they overlap in the test and comparison
data.


Installation
Install via PyPI:
pip install enrich_pvalues
Or install from github:
pip install https://github.com/TheFraserLab/enrich_pvalues/tarball/master
It should work with python 2 or 3, but python 3 is recommended.

Requirements
In requirements.txt, we use numpy, pandas, matplotlib, seaborn, tabulate,
and tqdm.



Usage
First, dump a configuration file to describe your data:
enrich_pvalues dump-config enrich_atac.json
This will also print a help table describing each option. You need to describe
your comparison data and your test data, and pick your p-value thresholds.
Next, split your comparison dataset into two tables: significant, and
not-significant:
enrich_pvalues split -c enrich_atac.json --prefix atac /path/to/comp_data.txt.gz
Now, run the enrichment using those two tables and your test data:
enrich_pvalues run -c enrich_atac.json -o atac_scores.xls -p atac /path/to/test_data.txt
Note, the second to last argument is the prefix from the second step.
Finally, plot the data. This can also be done by passing e.g. --plot myplot.png
to the run step.
enrich_pvalues plot --prefix caQTL atac_scores.xls atac_plot.pdf
Note: the scores can be excel format, pickled format, or text format, depending
on the suffix. Also, the prefix in this plot step is different, it is used to
title the plot only, and so can be whatever you want.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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