Selected the most variable CpGs per gene for clustering in both datasets.
Batch removed:
[[1]]
[1] "cg11262815" "cg11248413" "cg14182690" "cg06295404" "cg10990993"
[[2]]
[1] "CACNA1G" "NEUROG1" "RUNX3" "SOCS1" "MLH1"
Batch, age and gender removed:
[[1]]
[1] "cg11262815" "cg11248413" "cg14182690" "cg06295404" "cg10990993"
[[2]]
[1] "CACNA1G" "NEUROG1" "RUNX3" "SOCS1" "MLH1"
Heatmaps (left - batch removed, right - batch, age, gender; note: data weren't scaled before clustering)
pvclust didn't work on these datasets:
Error in solve.default(crossprod(X, X/vv)) :
Lapack routine dgesv: system is exactly singular
In addition: Warning message:
In lsfit(X, zz, 1/vv, intercept = FALSE) : 'X' matrix was collinear