Journal Article

<span class="smallCaps">qvality</span>: non-parametric estimation of <i>q</i>-values and posterior error probabilities

Lukas Käll, John D. Storey and William Stafford Noble

in Bioinformatics

Volume 25, issue 7, pages 964-966
Published in print April 2009 | ISSN: 1367-4803
Published online February 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp021

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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@cbr.su.se

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  1354 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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