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Bioinformatics Advance Access originally published online on February 4, 2009
Bioinformatics 2009 25(7):964-966; doi:10.1093/bioinformatics/btp021
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

QVALITY: non-parametric estimation of q-values and posterior error probabilities

Lukas Käll 1,2,*, John D. Storey 3 and William Stafford Noble 2,4

1Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Sweden, 2Department of Genome Sciences, University of Washington, Seattle, WA, 3Lewis-Sigler Institute, Princeton University, Princeton, NJ and 4Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA

*To whom correspondence should be addressed.


  Abstract

Summary: QVALITY is a C++ program for estimating two types of standard statistical confidence measures: the q-value, which is an analog of the p-value that incorporates multiple testing correction, and the posterior error probability (PEP, also known as the local false discovery rate), which corresponds to the probability that a given observation is drawn from the null distribution. In computing q-values, QVALITY employs a standard bootstrap procedure to estimate the prior probability of a score being from the null distribution; for PEP estimation, QVALITY relies upon non-parametric logistic regression. Relative to other tools for estimating statistical confidence measures, QVALITY is unique in its ability to estimate both types of scores directly from a null distribution, without requiring the user to calculate p-values.

Availability: A web server, C++ source code and binaries are available under MIT license at http://noble.gs.washington.edu/proj/qvality

Contact: lukas.kall{at}cbr.su.se

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Alfonso Valencia

Received on October 24, 2008; revised on December 23, 2008; accepted on January 7, 2009

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