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PGA: power calculator for case-control genetic association analyses

BACKGROUND: Statistical power calculations inform the design and interpretation of genetic association studies, but few programs are tailored to case-control studies of single nucleotide polymorphisms (SNPs) in unrelated subjects. RESULTS: We have developed the "Power for Genetic Association an...

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Detalles Bibliográficos
Autores principales: Menashe, Idan, Rosenberg, Philip S, Chen, Bingshu E
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2387159/
https://www.ncbi.nlm.nih.gov/pubmed/18477402
http://dx.doi.org/10.1186/1471-2156-9-36
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author Menashe, Idan
Rosenberg, Philip S
Chen, Bingshu E
author_facet Menashe, Idan
Rosenberg, Philip S
Chen, Bingshu E
author_sort Menashe, Idan
collection PubMed
description BACKGROUND: Statistical power calculations inform the design and interpretation of genetic association studies, but few programs are tailored to case-control studies of single nucleotide polymorphisms (SNPs) in unrelated subjects. RESULTS: We have developed the "Power for Genetic Association analyses" (PGA) package which comprises algorithms and graphical user interfaces for sample size and minimum detectable risk calculations using SNP or haplotype effects under different genetic models and study constrains. The software accounts for linkage disequilibrium and statistical multiple comparisons. The results are presented in graphs or tables and can be printed or exported in standard file formats. CONCLUSION: PGA is user friendly software that can facilitate decision making for association studies of candidate genes, fine-mapping studies, and whole-genome scans. Stand-alone executable files and a Matlab toolbox are available for download at:
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spelling pubmed-23871592008-05-20 PGA: power calculator for case-control genetic association analyses Menashe, Idan Rosenberg, Philip S Chen, Bingshu E BMC Genet Software BACKGROUND: Statistical power calculations inform the design and interpretation of genetic association studies, but few programs are tailored to case-control studies of single nucleotide polymorphisms (SNPs) in unrelated subjects. RESULTS: We have developed the "Power for Genetic Association analyses" (PGA) package which comprises algorithms and graphical user interfaces for sample size and minimum detectable risk calculations using SNP or haplotype effects under different genetic models and study constrains. The software accounts for linkage disequilibrium and statistical multiple comparisons. The results are presented in graphs or tables and can be printed or exported in standard file formats. CONCLUSION: PGA is user friendly software that can facilitate decision making for association studies of candidate genes, fine-mapping studies, and whole-genome scans. Stand-alone executable files and a Matlab toolbox are available for download at: BioMed Central 2008-05-13 /pmc/articles/PMC2387159/ /pubmed/18477402 http://dx.doi.org/10.1186/1471-2156-9-36 Text en Copyright © 2008 Menashe et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Menashe, Idan
Rosenberg, Philip S
Chen, Bingshu E
PGA: power calculator for case-control genetic association analyses
title PGA: power calculator for case-control genetic association analyses
title_full PGA: power calculator for case-control genetic association analyses
title_fullStr PGA: power calculator for case-control genetic association analyses
title_full_unstemmed PGA: power calculator for case-control genetic association analyses
title_short PGA: power calculator for case-control genetic association analyses
title_sort pga: power calculator for case-control genetic association analyses
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2387159/
https://www.ncbi.nlm.nih.gov/pubmed/18477402
http://dx.doi.org/10.1186/1471-2156-9-36
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