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Bioinformatics Advance Access published online on February 4, 2009
Bioinformatics, 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: Nonparametric 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, USA
3Lewis-Sigler Institute, Princeton University, Princeton, NJ, USA
4Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA

*To whom correspondence should be addressed. Prof. William Noble, E-mail: noble{at}gs.washington.edu


  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 thata 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 nonparametric 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: 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

Associate Editor: Alfonso Valencia

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

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