summary.vGWAS: Variance GWA Summary

In kullrich/vGWAS: Variance Heterogeneity Genome-wide Association Study - Reimplementation

Variance GWA Summary

Description

The function summarized the variance GWA result for the given scan object.

Usage

## S3 method for class 'vGWAS'
summary(object, nrMarkers = 10, ...)

Arguments

object	a result object from vGWAS scan. It can be any list or data.frame that contains chromosome, marker.map, and p.value, with class = 'vGWAS'. See vGWAS.
nrMarkers	a numeric value giving the number of top markers to be summarized.
...	not in use

Value

a summary for viewing vGWAS result.

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. PLoS Genetics, 8, e1002839.

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

package-vGWAS, vGWAS

Examples

# ----- 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, pB = FALSE)
# ----- visualize the scan ----- #
plot(vgwa)
summary(vgwa)
# ----- calculate the variance explained by the strongest marker ----- #
vGWAS.variance(phenotype = pheno,
marker.genotype = geno[, vgwa[["p.value"]] == min(vgwa[["p.value"]])])
# ----- genomic control ----- #
vgwa2 <- vGWAS.gc(vgwa)
plot(vgwa2)
summary(vgwa2)

kullrich/vGWAS documentation built on June 10, 2025, 3:56 a.m.