[R] [R-pkgs] New package: noia

[Arnaud Le Rouzic]

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 José M. Álvarez-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:
José M. Álvarez-Castro and Örjan 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.

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