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Get Top Features by PCA Dimension

get_top_pca_rotation.Rd

Interrogates the rotation in each dimension defined by dims and orders the features by the value of the principal components in that dimension. Each dimension is represented by a column of the resulting data frame.

Usage

get_top_pca_rotation(x, dims = 1:5L, n = 30L)

Arguments

x

A pca class object.

dims

integer(n). Vector of which dimensions to interrogate.

n

integer(1). The limit on how many features to report (i.e. the rows of the resulting data frame).

Value

A data frame of the top features ordered by the principal components given in the selected dimension.

Author

Stu Field, Michael R. Mehan

Examples

pca <- pca(pcapkg:::log10_ft(simdata))
get_top_pca_rotation(pca, n = 10L)
#> # A tibble: 10 × 5
#>    PC1   PC2   PC3   PC4   PC5  
#>    <chr> <chr> <chr> <chr> <chr>
#>  1 7     5     8     36    31   
#>  2 9     33    37    37    19   
#>  3 10    23    14    32    14   
#>  4 15    4     27    39    40   
#>  5 6     22    38    3     21   
#>  6 19    3     28    28    33   
#>  7 37    13    20    21    22   
#>  8 29    30    18    6     9    
#>  9 5     18    25    24    1    
#> 10 22    35    4     33    11