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Valentin Wimmer authored and gaborcsardi committed Mar 12, 2012
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25 changes: 25 additions & 0 deletions DESCRIPTION
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Package: synbreedData
Type: Package
Title: Data for the synbreed package
Version: 1.1
Date: 2012-03-12
Author: Valentin Wimmer, Theresa Albrecht, Hans-Juergen Auinger,
Chris-Carolin Schoen with contributions by Malena Erbe, Ulrike
Ober and Christian Reimer
Depends: R (>= 2.10)
Maintainer: Valentin Wimmer <Valentin.Wimmer@wzw.tum.de>
Description: This package contains three data sets from cattle, maize
and mice to illustrate the functions in the synbreed R package.
All data sets are stored in the gpData format introduced in the
synbreed package. This research was funded by the German
Federal Ministry of Education and Research (BMBF) within the
AgroClustEr Synbreed - Synergistic plant and animal breeding
(FKZ 0315528A).
URL: http://synbreed.r-forge.r-project.org/
License: GPL-2
LazyLoad: yes
LazyData: no
ZipData: no
Packaged: 2012-03-12 10:50:03 UTC; Valentin
Repository: CRAN
Date/Publication: 2012-03-14 17:27:52
13 changes: 13 additions & 0 deletions MD5
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3e9750c12b8caee9b38b754e61b20fa4 *DESCRIPTION
7a19fee4c642dcdee75ed9e371a6043e *NAMESPACE
dd26069eade37e93aed5e63fec6c3151 *data/cattle.R
614789a84bd4a86af3b812c2eccaa461 *data/cattle.RData
ea08d460d9d590202bd0edf1e0e76755 *data/datalist
2b3fc86749ab35dce0338ae30bcc29c7 *data/maize.R
fe8703ef01ff821e41baa4fd2a27ead6 *data/maize.RData
774f5c04fe2c1a4ed1350a6606f51baa *data/mice.R
0db0b312e2044790a4ab0a2b1ea8d0e6 *data/mice.RData
c31e4d100b9ded4f8188a3ba465c2840 *inst/CITATION
9507505d37aa18e89d8d65a3b4d721a6 *man/cattle.Rd
b8e39bccc14846842dbdc908b53197ac *man/maize.Rd
cd80567633c43db491167d7a3566fb4e *man/mice.Rd
5 changes: 5 additions & 0 deletions NAMESPACE
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# Default NAMESPACE created by R
# Remove the previous line if you edit this file

# Export all names
exportPattern(".")
1 change: 1 addition & 0 deletions data/cattle.R
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load("cattle.RData")
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3 changes: 3 additions & 0 deletions data/datalist
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cattle
maize
mice
1 change: 1 addition & 0 deletions data/maize.R
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load("maize.RData")
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load("mice.RData")
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19 changes: 19 additions & 0 deletions inst/CITATION
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if (!exists("meta") || is.null(meta)) meta <- packageDescription("synbreed")

citHeader("To cite package", sQuote(meta$Package), "in publications use:")

### Default citation of R packages
year <- sub(".*(2[[:digit:]]{3})-.*", "\\1", meta$Date)
vers <- paste("R package version", meta$Version)
title <- paste(meta$Package, ": ", meta$Title, sep = "")
citEntry(
entry = "Manual",
title = title,
author = as.personList(meta$Author),
year = year,
note = vers,
url = meta$URL,
textVersion = paste(meta$Author, " (", year, "). ", title, ". ",
vers, ". ", meta$URL, sep = "")
)

32 changes: 32 additions & 0 deletions man/cattle.Rd
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\name{cattle}
\alias{cattle}
\docType{data}
\title{
Dairy cattle data
}
\description{
Data set contains genotypic, phenotypic, map and pedigree data of 500 bulls. All individuals are labeled with an unique ID, starting with ID1430 and ending with ID1929. Genotypic and pedigree data is based on a real cattle data set while phenotypes were built artificially. Pedigree information is available at least on parents and grandparents of the phenotyped individuals.

There are two quantitative phenotypes available. The heritabilities of these traits are 0.41 and 0.66, estimated with a pedigree-based animal model using the data set on hand.

Genotypic data consists of 7250 biallelic SNP markers for every phenotyped individual with missing data included. SNPs are mapped across all 29 autosomes. Distances in the SNP map are given in mega bases (Mb).
}
\usage{data(cattle)}
\format{
Object of class \code{gpData}
}
%%\details{
%% ~~ If necessary, more details than the __description__ above ~~
%%}
%%\source{
%% ~~ reference to a publication or URL from which the data were obtained ~~
%%}

\examples{
\dontrun{
library(synbreed)
data(cattle)
summary(cattle)
}
}
\keyword{datasets}
27 changes: 27 additions & 0 deletions man/maize.Rd
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\name{maize}
\alias{maize}
\docType{data}
\title{
Simulated maize data
}
\description{
This is a simulated dataset of a maize breeding program. Data comprises 1250 doubled haploid (DH) lines that were genotyped with 1117 polymorphic SNP markers and phenotyped in a testcross with a single tester for one quantitative trait. All individuals are labeled with a unique ID, starting from 11360 to 12609. Markers are distributed along all 10 chromosomes of maize. Pedigree information starts with basis population and is available up to 15 generations. The 1250 lines belong to 25 full sib families with 50 individuals in each family. In the simulation of true breeding values (TBV), 1000 biallelic quantitative trait loci (QTL) with equal and additive (no dominance or epistasis) effects were generated. True breeding values for individuals were calculated according to
\deqn{tbv=\sum_{k=1}^{1000} QTL_k}{TBV=\sum QTL(k)}
where \eqn{QTL_k}{QTL(k)} is the effect of the \eqn{k}-th QTL. Phenotypic values were simulated according to
\deqn{y_i=tbv_i + \epsilon_i}{trait=tbv+e}
where \eqn{\epsilon_i \sim N(0,\sigma^2)}{e = N(0,sigma2)}. The value for \eqn{\sigma^2}{sigma2} was chosen in a way that a given plot heritability of \eqn{h^2=0.197}{h2=0.197} is realized. Note that true breeding values for 1250 phenotyped lines are stored as \code{tbv} in \code{covar} of \code{gpData} object. Reported phenotypic values of lines are adjusted values testcross means for yield [dt/ha] evaluated in 3 locations.
}
\usage{data(maize)}
\format{
Object of class \code{gpData}
}

\examples{
\dontrun{
library(synbreed)
data(maize)
summary(maize)
}
}
\keyword{datasets}

35 changes: 35 additions & 0 deletions man/mice.Rd
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\name{mice}
\alias{mice}
\docType{data}
\title{
Heterogenous stock mice population
}
\description{
Data set comprises public available data of 2527 (1293 males and 1234 females) heterogenous stock mice derived from eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J and LP/J) followed by 50 generations of pseudorandom mating. All individuals are labeled with a unique ID, starting with \code{A048005080}. For all individuals, family, sex (females=0, males=1), month of birth (1-12), birthyear, coat color, cage density and litter is available and stored in \code{covar}.

The measured traits are described in Solberg et al. (2006). Here, the body weight at age of 6 weeks [g] and growth slope between 6 and 10 weeks age [g/day] are available. The heritabilities of these traits are reported as 0.74 and 0.30, respectively (Valdar et al, 2006b). Phenotypic data was taken from \url{http://mus.well.ox.ac.uk/GSCAN/HS_PHENOTYPES/Weight.txt}.

Genotypic data consists of 12545 biallelic SNP markers and is available for 1940 individuals. Raw genotypic data from \url{http://mus.well.ox.ac.uk/GSCAN/HS_GENOTYPES/All} is given in the \code{Ped-File Format} with two columns for each marker. Both alleles were combined to a single genotype for each marker in \code{mice} data. The SNPs are mapped in a sex-averaged genetic map with distances given in centimorgan (Shifman et al. (2006)). SNPs are mapped across all 19 autosomes and X-chromosome where distances between adjacent markers vary form 0 to 3 cM.
}
\usage{data(mice)}
\format{
Object of class \code{gpData}
}
\source{Welcome Trust Centre for Human Genetics, Oxford University, data available from \url{http://gscan.well.ox.ac.uk}}
\references{
Shifman S, Bell JT, Copley RR, Taylor MS, Williams RW, et al. (2006) A High-Resolution Single Nucleotide Polymorphism Genetic Map of the Mouse Genome. PLoS Biol 4(12)

Solberg L.C. et al. (2006), A protocol for high-throughput phenotyping, suitable for quantitative trait analysis in mice. Mamm. Genome 17, 129-146

Valdar W, Solberg LC, Gauguier D, Burnett S, Klenerman P, Cookson WO, Taylor MS, Rawlins JN, Mott R, Flint J. (2006a) Genome-wide genetic association of complex traits in heterogeneous stock mice. Nat Genet. 8, 879-887.

Valdar W, Solberg LC, Gauguier D, Cookson WO, Rawlins NJ, Mott R, Flint J.(2006b) Genetic and environmental effects on complex traits in mice. Genetics 175, 959-984
}
\examples{
\dontrun{
library(synbreed)
data(mice)
summary(mice)
}
}
\keyword{datasets}

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