designGG: an R-package and web tool for the optimal design of genetical genomics experiments View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2009-06-18

AUTHORS

Yang Li, Morris A Swertz, Gonzalo Vera, Jingyuan Fu, Rainer Breitling, Ritsert C Jansen

ABSTRACT

BackgroundHigh-dimensional biomolecular profiling of genetically different individuals in one or more environmental conditions is an increasingly popular strategy for exploring the functioning of complex biological systems. The optimal design of such genetical genomics experiments in a cost-efficient and effective way is not trivial.ResultsThis paper presents designGG, an R package for designing optimal genetical genomics experiments. A web implementation for designGG is available at http://gbic.biol.rug.nl/designGG. All software, including source code and documentation, is freely available.ConclusionDesignGG allows users to intelligently select and allocate individuals to experimental units and conditions such as drug treatment. The user can maximize the power and resolution of detecting genetic, environmental and interaction effects in a genome-wide or local mode by giving more weight to genome regions of special interest, such as previously detected phenotypic quantitative trait loci. This will help to achieve high power and more accurate estimates of the effects of interesting factors, and thus yield a more reliable biological interpretation of data. DesignGG is applicable to linkage analysis of experimental crosses, e.g. recombinant inbred lines, as well as to association analysis of natural populations. More... »

PAGES

188

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2105-10-188

DOI

http://dx.doi.org/10.1186/1471-2105-10-188

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029824375

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/19538731


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