Description Usage Arguments Value Author(s) References See Also Examples
Variance Genome-wide association for using nonparametric variance test
1 2 | vGWAS(phenotype, geno.matrix, kruskal.test = FALSE,
marker.map = NULL, chr.index = NULL)
|
phenotype |
a |
geno.matrix |
a |
kruskal.test |
a |
marker.map |
a |
chr.index |
a |
a data.frame
containing columns of marker
names, chromosome
indices, marker.map
positions, test statistic
values, and p.value
for each position.
Xia Shen
Shen, X., Pettersson, M., Ronnegard, L. and Carlborg, O. (2011): Inheritance beyond plain heritability: variance-controlling genes in Arabidopsis thaliana. Submitted.
Ronnegard, L., Shen, X. and Alam, M. (2010): hglm: A Package for Fitting Hierarchical Generalized Linear Models. The R Journal, 2(2), 20-28.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ## Not run:
# ----- load data ----- #
data(pheno)
data(geno)
data(chr)
data(map)
# ----- variance GWA scan ----- #
vgwa <- vGWAS(phenotype = pheno, geno.matrix = geno,
marker.map = map, chr.index = chr)
# ----- visualize the scan ----- #
plot(vgwa)
summary(vgwa)
# ----- calculate the variance explained by strongest the marker ----- #
vGWAS.heritability(phenotype = pheno,
marker.genotype = geno[,vgwa$p.value == min(vgwa$p.value)])
# ----- genomic control ----- #
vgwa2 <- vGWAS.gc(vgwa)
plot(vgwa2)
summary(vgwa2)
## End(Not run)
|
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