Get significant principal components
Usage
get_sig_pcs(x, pc_method = c("mp", "gd"), verbose = FALSE)
Arguments
- x
A data frame or matrix of methylation values; rows = features, columns = samples
- pc_method
String indicating the method for estimating dimension; "gd" = Gavish-Donoho (default), "mp" = Marchenko-Pastur
- verbose
Boolean; print output statements
Value
List containing four elements; sig_pcs = significant PCs, percent_var = percent variance explained, loadings = PC loadings, est_dim = estimated dimension
Examples
x <- diag(4)
get_sig_pcs(x, "gd")
#> $sig_pcs
#> PC1
#> 1 6.952263e-17
#> 2 7.715167e-01
#> 3 -1.543033e-01
#> 4 -6.172134e-01
#>
#> $percent_var
#> PC1
#> percent_variance_explained 0.3333333
#>
#> $loadings
#> PC1
#> 1 5.192593e-17
#> 2 7.715167e-01
#> 3 -1.543033e-01
#> 4 -6.172134e-01
#>
#> $est_dim
#> [1] 1
#>