Hi the list, A new version (0.92) of my package 'noia' will be available soon on CRAN mirrors, and I think it might be a good opportunity to introduce it shortly to the R community. In summary: 'noia' will be of absolutely no interest for 99.99% of you. The 0.01% remaining are quantitative geneticists who are interested in measuring the effect of genes in a proper way. Since some of you may want to know why it is worth to let this 'noia' package take a few bytes on the CRAN server, I will try to introduce very shortly the scientific problem. The rules that explain the transmission of genes between generations are well known since the end of the 19th century. One important consequence of these rules is that in all diploid organisms (having two copies of the genomes, i.e. most of them, including us), it is virtually impossible to produce an equal number of offspring of each "type" from non-inbred parents: you end up, most of the time, with frequencies such as 1/4 vs 3/4, or 7/16 vs 9/16, or many other combinations. For quantitative traits, the link between the genes and the characters is complex, and the effect of genes has to be measured through models that look like cross-factor ANOVA designs. Because of the unequal segregating ratios, these ANOVAs are highly unbalanced, with all well-known annoying consequences: correlations between effect estimates, non-orthogonal variance decomposition, etc. For a long time, comparing estimates measured in differently designed populations was not considered as a big issue. However, the recent need of effective model selection procedures lead to the proposition of new models aiming to a (more or less) orthogonal decomposition of genetic effects. This package provides tools to perform linear regressions using various models, to manipulate the genetic effects, and to compute genotype to phenotype maps, i.e. the function explaining how the genes expresses a given character. In addition, the 'noia' package provides a tool to perform 'multilinear' regression, an attempt of non-linear genotype-phenotype mapping. In summary, 'noia' is a wrapper for lm() and nls() functions in a very specific context: estimating the effects of genes on a given trait. NB: 'noia' is useless if the location of the genes is not known. Locating the genes requires a QTL detection procedure, for which packages already exist (see Rqtl for instance). Much more information can be found in scientific publications. Two are particularly relevant: * This package and its functions are described in a recent paper: Arnaud Le Rouzic and Jos? M. ?lvarez-Castro, Estimation of Genetic Effects and Genotype-Phenotype Maps, /Evolutionary Bioinformatics /2008:4 225-235. http://la-press.com/article.php?article_id=887 * The corresponding statistical framework is extensively described in: Jos? M. ?lvarez-Castro and ?rjan Carlborg, A unified model for functional and statistical epistasis and its application in QTL analysis, Genetics, Vol. 176, 1151-1167 2007. http://www.genetics.org/cgi/content/abstract/176/2/1151 Given the probable low impact of the package, I am not planning to follow the R help mailing list. However, my email address is everywhere in the manual, and I would be very happy to answer questions related to this package; so don't hesitate to forward potential questions or to encourage users to contact me directly. Arnaud Le Rouzic. _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages