MetaP, a program to combine P values

MetaP: a program to combine P values

>>> Click here to start the program.

The first start-up of this program may take minutes.

If you use this software tool in published work, please kindly cite it:

Software: MetaP
Author: Dongliang Ge, PhD
URL: http://people.genome.duke.edu/~dg48/metap.php

References:

Whitlock, M. C. Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach. J Evol Biol 18, 1368-73 (2005).

Acknowledgments

The author would like to thank Dr. Mike Weale at UCL and Dr. David B. Goldstein at Duke IGSP Center for Human Genome Variation for the help and support in the development of this software. The development of this software tool is also supported by Duke Institute for Genome Sciences & Policy, and Center for HIV/AIDS Vaccine Immunology. This software tool uses a JAVA library SSJ (Stochastic Simulation in Java) developed by a number of colleagues at the Universite de Montreal.

For questions and comments, contact the author at:d.ge@duke.edu

This software tool is free for public uses. The author keeps all the copyright.

FAQ

What does this program do?

MetaP performs a meta-analysis and combines the statistical association signals (P values) from independent studies or study populations, taking account of the impacts of sample sizes and effect directions.

What is the system requirement to run this program?

MetaP is a JAVA applet. It needs your internet browser to be JAVA-enabled - which is usually (if not always) true in today's computer. To test whether java is working in your browser, here is a useful link: http://www.java.com/en/download/help/testvm.xml

Which combined P value should I choose from the output?

MetaP outputs four different combined P values, using different levels of avilable information:

Conventional Fisher's: only considers P values;

Fisher's trend: considers P values and effect directions;

Stouffer's z: considers P values and sample sizes;

Stouffer's z trend: considers P values, sample sizes, and effect directions.

Geneally speaking you should look at the P value corrected for as many as factors as allowed by your data. That is, if you have both sample size and effect direction information available, the Stouffer's z trend is probably the most accurate one to look at.

2009 Dongliang Ge, PhD