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Bioinformatics Advance Access originally published online on November 28, 2008
Bioinformatics 2009 25(2):272-273; doi:10.1093/bioinformatics/btn616
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© 2008 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.

Programs for calculating the statistical powers of detecting susceptibility genes in case–control studies based on multistage designs

Nobutaka Kitamura 1,*, Kouhei Akazawa 1, Akinori Miyashita 2, Ryozo Kuwano 2, Shin-ichi Toyabe 1, Junichiro Nakamura 1, Norihito Nakamura 1, Tatsuhiko Sato 1 and M. Aminul Hoque 3

1Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata 951-8520, 2Genome Science Branch, Center of Bioresource-Based Researches, Brain Research Institute, Niigata University, Niigata 951-8585, Japan and 3Department of Statistics, University of Rajshahi, Rajshahi-6205, Bangladesh

*To whom correspondence should be addressed.


  Abstract

Motivation: A two-stage association study is the most commonly used method among multistage designs to efficiently identify disease susceptibility genes. Recently, some SNP studies have utilized more than two stages to detect disease genes. However, there are few available programs for calculating statistical powers and positive predictive values (PPVs) of arbitrary n-stage designs.

Results: We developed programs for a multistage case–control association study using R language. In our programs, input parameters include numbers of samples and candidate loci, genome-wide false positive rate and proportions of samples and loci to be selected at the k-th stage (k=1,..., n). The programs output statistical powers, PPVs and numbers of typings in arbitrary n-stage designs. The programs can contribute to prior simulations under various conditions in planning a genome-wide association study.

Availability: The R programs are freely available for academic users and can be downloaded from http://www.med.niigata-u.ac.jp/eng/resources/informatics/gwa.html

Contact: nktmr{at}m12.alpha-net.ne.jp

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Alfonso Valencia

Received on June 5, 2008; revised on November 14, 2008; accepted on November 24, 2008

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