cross.read.cross(format=c("csv","mm","gary","karl"), ...)"csv",
"mm", "gary", or "karl").cross, which is a list with two components:names(geno) contains the names of the
chromsomes.
Each chromosome is itself a list, and is given class
A or X according to whether it is autosomal
or the X chromosome.
There are two components for each chromosome:
data, a matrix whose rows are individuals and whose
columns are markers
map, either a vector of marker
positions (in cM) or a matrix of dim (2 x n.mar) where the rows
correspond to marker positions in female and male genetic distance,
respectively.
The genotype data for a backcross is coded as follows: 0 = missing,
1 = AA, 2 = AB.
For an F2 intercross, the coding is 0 = missing, 1 = AA, 2 = AB, 3
= BB, 4 = not BB (ie AA or AB; D in mapmaker/qtl), 5 = not AA (ie AB
or BB; C in mapmaker/qtl).
For a 4-way cross, the mother and father are assumed to have
genotypes AB and CD, respectively. The genotype data for the
progeny is assumed to be phase-known, with the following coding
scheme: 0 = missing, 1 = AC, 2 = BC, 3 = AD, 4 = BD, 5 = A = AC or AD,
6 = B = BC or BD, 7 = C = AC or BC, 8 = D = AD or BD, 9 = AC or BD,
10 = AD or BC.n.ind x n.phe) containing the
phenotypesread.cross.csv,
read.cross.mm, read.cross.gary,
or read.cross.karl, according to the specified
format.read.cross.csv, read.cross.gary,
read.cross.mm, read.cross.karl,
fake.bc, fake.f2,
fake.4way, listeria,
hypercross1 <- read.cross("karl",dir="Data", genfile="gen.txt",
phefile="phe.txt", mapfile="map.txt")Run the code above in your browser using DataLab