vGWAS: Variance Genome-wide Association

Description Usage Arguments Value Author(s) References See Also Examples

Description

Variance Genome-wide association for using nonparametric variance test

Usage

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vGWAS(phenotype, geno.matrix, kruskal.test = FALSE, 
      marker.map = NULL, chr.index = NULL)

Arguments

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.

Value

a data.frame containing columns of marker names, chromosome indices, marker.map positions, test statistic values, and p.value for each position.

Author(s)

Xia Shen

References

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.

See Also

vGWAS-package

Examples

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## 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)

vGWAS documentation built on May 2, 2019, 6:48 p.m.