Converts p-values to q-values

This Python package implements qvalue and pi0 estimation from Storey and Tibshirani (2003).

The only function that needs to be called is 'qvalue()'. It will accept a numpy array of pvalues and will return a numpy array of qvalues. For instance, given some uniform p-values:

import numpy as np 
from qvalue.qvalue import qvalue, pi0est, plot_qvalue

pv = np.random.uniform(0.0, 1.0, size = (1000,))

it's possible to convert them in q-values by calling

qv, pi0 = qvalue(pv)

qvalue() also includes a memory-efficient (but not CPU-efficient) procedure for the case when it's not possible to store both the p-values and the q-values in memory at the same time. In addition it's possible to change the number of hypotheses tested (m) or the proportion of null hypotheses (pi0).

pi0() estimates the proportion of null hypotheses:

pi0 = pi0est(pv)

Visualize the q-value and p-values with:

plot_qvalue(qv,pv)

Installation

Install this repo:

pip install --upgrade https://github.com/ncchung/qvalue-python/tarball/master

References

Storey, J. D., & Tibshirani, R. (2003). Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences, 100(16), 9440-9445.