vGWAS: Variance Genome-wide Association
In vGWAS: Variance Heterogeneity Genome-Wide Association Study

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 `numeric` or `logical` vector of the phenotyic values. See Examples.
`geno.matrix`	a `matrix` or `data.frame` with individuals as rows and markers as columns. The marker genotypes for each marker are coded as one column. See Examples.
`kruskal.test`	a `logical` value specifying whether to use Kruskal-Wallis statistic. The default option is `FALSE`, i.e., the usual ANOVA statistic is used in place of Kruskal-Wallis statistic.
`marker.map`	a `numeric` vector giving the marker map positions for each chromosome. See Examples.
`chr.index`	a `numeric` vector giving the chromosome index for each marker. See Examples.

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.

vGWAS-package

## 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)