M value: why I decided to split the probes into "red" and "green"
SVD on the entire 27k by 511 patients M value matrix, plot 1st eigenarray (u matrix) and "color" the points according to the dye with with each CpG was labeled:
M value: analysis of red probes, identification of adjustment variables
Correlation of the red probes, first four eigengenes with the batch effect:
kruskal.test(mredsvd$v[,2],as.factor(batch))
Kruskal-Wallis rank sum test
data: mredsvd$v[, 2] and as.factor(batch)
Kruskal-Wallis chi-squared = 10.8903, df = 12, p-value = 0.5383
kruskal.test(mredsvd$v[,3],as.factor(batch))
Kruskal-Wallis rank sum test
data: mredsvd$v[, 3] and as.factor(batch)
Kruskal-Wallis chi-squared = 21.7447, df = 12, p-value = 0.04048
kruskal.test(mredsvd$v[,4],as.factor(batch))
Kruskal-Wallis rank sum test
data: mredsvd$v[, 4] and as.factor(batch)
Kruskal-Wallis chi-squared = 35.8388, df = 12, p-value = 0.0003439
After removing the batch effect p-value for the association of the first principal component with the batch is 0.7748.