Calculate correspondence analysis row and column coordinates.
ca_coords.Rd`ca_coords` calculates the standardized and principal coordinates of the rows and columns in CA space.
Arguments
- caobj
A "cacomp" object as outputted from `cacomp()`.
- dims
Integer indicating the number of dimensions to use for the calculation of coordinates. All elements of caobj (where applicable) will be reduced to the given number of dimensions. Default NULL (keeps all dimensions).
- princ_coords
Integer. Number indicating whether principal coordinates should be calculated for the rows (=1), columns (=2), both (=3) or none (=0). Default 3.
- princ_only
Logical, whether only principal coordinates should be calculated. Or, in other words, whether the standardized coordinates are already calculated and stored in `caobj`. Default `FALSE`.
Value
Returns input object with coordinates added. std_coords_rows/std_coords_cols: Standardized coordinates of rows/columns. prin_coords_rows/prin_coords_cols: Principal coordinates of rows/columns.
Details
Takes a "cacomp" object and calculates standardized and principal coordinates for the visualization of CA results in a biplot or to subsequently calculate coordinates in an Association Plot.
Examples
# Simulate scRNAseq data.
cnts <- data.frame(cell_1 = rpois(10, 5),
cell_2 = rpois(10, 10),
cell_3 = rpois(10, 20))
rownames(cnts) <- paste0("gene_", 1:10)
cnts <- as.matrix(cnts)
# Run correspondence analysis.
ca <- cacomp(obj = cnts, princ_coords = 1)
#> Warning:
#> Parameter top is >nrow(obj) and therefore ignored.
#> No dimensions specified. Setting dimensions to: 2
#> Please consider setting the dimensions to a lower value to speed up the calculation.
#> Recommended dimensionality: << min(nrows, ncols) * 0.2
ca <- ca_coords(ca, princ_coords = 3)