DCEG Study Design Tools: Power for Genetic Association Analyses (PGA)
, by DCEG Staff
by Vicky A. Perez, M.A., M.S.
DCEG scientists have developed an extensive collection of tools to aid other researchers with study design and planning, data collection and analysis, and risk assessment. These tools are available free for download from the DCEG website.
Among these tools is Power for Genetic Association Analyses (PGA), a user-friendly software package designed to aid decision making for the design of association studies of candidate genes, fine-mapping studies, and whole-genome scans. The tool was developed by Philip S. Rosenberg, Ph.D., senior investigator in the Biostatistics Branch, with colleagues Drs. Idan Menashe and Bingshu Chen. PGA has been downloaded 260 times over the past year, making it one of DCEG’s most downloaded tools. "The tool is widely used, which is very gratifying," said Dr. Rosenberg.
The team developed PGA to perform the power calculations necessary to determine sample sizes in case-control genetic association studies. Power analysis is used to estimate the sample size needed to reasonably detect an effect—an important step in study design—as well as to interpret study results.
Before PGA, most computational tools that were commonly used in genetic association studies were designed for family-based studies. However, these tools had limited capability in performing the power calculations necessary to assess genetic associations of single nucleotide polymorphisms (SNPs) in general population studies. "I believe our tool set is an early and very sophisticated example of what user-friendly software can achieve—one that is now being emulated by the web-based tools being developed collaboratively by DCEG investigators and our colleagues at the NCI Center for Biomedical Informatics & Information Technology (CBIIT)," said Rosenberg.
For PGA, Drs. Rosenberg, Menashe, and Chen developed algorithms and graphical user interfaces (GUIs) that calculate the sample size and the minimum detectable risk in genetic case-control studies for dominant, co-dominant, and recessive models of SNPs and SNP haplotypes. The GUIs can display multiple sample-size scenarios simultaneously and produce graphs and tables for printing or exporting in standard file formats.
The source code was developed in MATLAB® and compiled so users can easily download and install the GUIs as a stand-alone application in Windows.
Reference
Menashe I, Rosenberg PS, Chen BE. PGA: Power calculator for case-control genetic association analyses. BMC Genetics 2008 May 13; 9:36. doi: 10.1186/1471-2156-9-36.