Simulated data set from a F2 population.
data("onemap_example_f2")The format is: List of 10 $ geno : num [1:200, 1:66] 1 3 2 2 1 0 3 1 1 3 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:200] "IND1" "IND2" "IND3" "IND4" ... .. ..$ : chr [1:66] "M1" "M2" "M3" "M4" ... $ n.ind : int 200 $ n.mar : int 66 $ segr.type : chr [1:66] "A.H.B" "C.A" "D.B" "C.A" ... $ segr.type.num: num [1:66] 1 3 2 3 3 2 1 3 2 1 ... $ n.phe : int 1 $ pheno : num [1:200, 1] 37.6 36.4 37.2 35.8 37.1 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : NULL .. ..$ : chr "Trait_1" $ CHROM : NULL $ POS : NULL $ input : chr "/home/cristiane/R/x86_64-pc-linux-gnu-library/3.4/onemap/extdata/onemap_example_f2.raw" - attr(*, "class")= chr [1:2] "onemap" "f2"
A total of 200 individuals were genotyped for 66 markers (36
co-dominant, i.e. a, ab or b and 30 dominant i.e. c or a and d or b) with 15% of missing data.
There is one quantitative phenotype to show how
to use onemap output as R\qtl and QTL Cartographer input. Also, it is used
for the analysis in the tutorial that comes with OneMap.
data(onemap_example_f2)
plot(onemap_example_f2)
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