GNU R package for fine-mapping complex diseases

 Most phenotypes of medical importance can be measured quantitatively,
 and in many cases the genetic contribution is substantial, accounting
 for 40% or more of the phenotypic variance. Considerable efforts have
 been made to isolate the genes responsible for quantitative genetic
 variation in human populations, but with little success, mostly
 because genetic loci contributing to quantitative traits
 (quantitative trait loci, QTL) have only a small effect on the
 phenotype. Association studies have been proposed as the most
 appropriate method for finding the genes that influence complex
 traits. However, family-based studies may not provide the resolution
 needed for positional cloning, unless they are very large, while
 environmental or genetic differences between cases and controls may
 confound population-based association studies.
 .
 These difficulties have led to the study of animal models of human
 traits. Studies using experimental crosses between inbred animal
 strains have been successful in mapping QTLs with effects on a number
 of different phenotypes, including behaviour, but attempts to
 fine-map QTLs in animals have often foundered on the discovery that a
 single QTL of large effect was in fact due to multiple loci of small
 effect positioned within the same chromosomal region. A further
 potential difficulty with detecting QTLs between inbred crosses is
 the significant reduction in genetic heterogeneity compared to the
 total genetic variation present in animal populations: a QTL
 segregating in the wild need not be present in the experimental
 cross.
 .
 The idea behind this package is that when multiple strains of
 animals that differ in their susceptibility to multiple diseases
 are bread over multiple generations, then one can analyse the
 contribution that a particular genetic locus has to each of those
 diseases. While in the past this approach has been performed
 for one disease at a time, this tool extends the statistics
 for allowing multiple crosses and thus save animal lifes. A larger
 stock of animals with more generations to keep them will further
 help producing larger numbers of observable cross-over events
 and thus help increasing the resolution of the mapping.
 .
 Happy is an R interface into the HAPPY C package for fine-mapping
 Quantitative Trait Loci (QTL) in Heterogenous Stocks (HS). An HS is
 an advanced intercross between (usually eight) founder inbred strains
 of mice. HS are suitable for fine-mapping QTL.  It uses a multipoint
 analysis which offers significant improvements in statistical power to
 detect QTLs over that achieved by single-marker association.
 .
 The happy package is
 an extension of the original C program happy; it uses the C code to
 compute the probability of descent from each of the founders, at each
 locus position, but the happy packager allows a much richer range of
 models to be fit to the data.