Description Usage Arguments Details Value Author(s) References Examples
The function computes an analysis of variance with a sire effect and a dose haplotype effect.
1 2 3 | haplomax.HS.add(hap.chrom1.pere, hap.chrom2.pere, hap.trans.pere,
hap.trans.mere, perf, CD, genea, map, marq.hap)
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hap.chrom1.pere |
character matrix (number of sires x number of markers) which gives the haplotype of the first chromosome for each sire. |
hap.chrom2.pere |
character matrix (number of sires x number of markers) which gives the haplotype of the second chromosome for each sire. |
hap.trans.pere |
numeric matrix (number of individuals x number of markers) which provides, for each individual, the haplotype transmitted by its father. |
hap.trans.mere |
numeric matrix (number of individuals x number of markers) which provides, for each individual, the haplotype transmitted by its mother. |
perf |
numeric vector of length=number of individuals which contains the performances of individuals. |
CD |
numeric vector of length=number of individuals which contains the CD of individuals. var(perf$_i$)=error variance/CD$^2_i$ |
genea |
numeric matrix (number of individuals x 2) which contains the progeny index and its father index. |
map |
numeric vector of length=(number of markers-1) which contains the distance in Morgan between two consecutive markers on the chromosome. |
marq.hap |
number of markers of the mutated haplotype. |
Progeny information have to be ranged in the same order in genea, hap.trans.pere, hap.trans.mere, perf and CD.
Sire information have to be ranged in the same order in unique(genea[,2]), hap.chrom1.pere and hap.chrom2.pere.
All distances are assumed to be Haldame's distance in Morgan.
Test positions are located on the middles of marq.hap marker sliding windows.
The returned value is a data frame which contains 5 columns:
-Test positions
-Value of Fisher test
-Mutated (i.e. associated to Q allele) haplotype
-Estimate of the error variance
-Estimate of the Q allele effect
S. Dejean, N. Oumouhou, D. Estivals, B. Mangin
publication to be submitted: C. Cierco-Ayrolles, S. Dejean, A. Legarra, H. Gilbert, T. Druet, F. Ytournel, D. Estivals, N. Oumouhou and B. Mangin. Combining linkage analysis and linkage disequilibrium for QTL fine mapping in animal pedigrees.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | data(data.test)
map=data.test[[1]]
hap.trans.mere=data.test[[2]]
hap.trans.pere=data.test[[3]]
hap.chrom1.pere=data.test[[4]]
hap.chrom2.pere=data.test[[5]]
perf=data.test[[6]]
CD=data.test[[7]]
genea=data.test[[9]]
# In this example, marker positions are : 0, 0.010, 0.020, 0.030, 0.040, 0.050, 0.060,
# 0.070, 0.080, 0.090.
# we use a 2 markers-associated haplotype
marq.hap=2
haplomax.HS=haplomax.HS.add(hap.chrom1.pere,hap.chrom2.pere,hap.trans.pere,hap.trans.mere,
perf,CD,genea,map,marq.hap)
haplomax.HS
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