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Process vertebral measurements and PC scores of traditional morphometric data

Source: R/process_input.R
process_PC.Rd

process_PC() initializes the analysis workflow by processing a dataset of vertebral measurements and already computed PC scores into an object usable by MorphoRegions. Such processing includes identifying the vertebra indices, measurements, and PC scores.

Usage

process_PC(data, pos = 1L, pcscores, eigenvals, posPC)

Arguments

data

a data frame containing a column of vertebra indices and measurements for each vertebra, or a named list thereof for multiple specimens with the names of the list corresponding to the unique identifiers of each specimen.

pos

the name or index of the variable in data containing the vertebra indices. Default is to use the first column.

pcscores

a matrix or data frame containing PC scores of each vertebra. Note that for multiple specimens, an ordination method should have been performed on the concatenated data across all specimens so that pcscores is a single data frame or matrix containing scores for all specimens.

eigenvals

a numeric vector containing the eigenvalues of each PC axis.

posPC

a vector containing the positional information of vertebrae in pcscores, or a named list thereof for multiple specimens with the names of the list corresponding to the unique identifiers of each specimen. If not provided, will assume the row order of pcscores matches the vertebra order in pos.

Value

A regions_pco object, which contains user-provided eigenvectors in the scores component and eigenvalues in the eigen.val component. The original dataset, including positional information, is stored in the data attribute.

Details

Unlike process_measurements(), process_PC() does not fill in missing values and these should have been removed or replaced by numeric values before running process_PC().

See also

  • process_gmPC() for processing PC scores from 2D or 3D geometric morphometric datasets

  • svdPCO() for computing principal coordinate axes from processed vertebra data.

  • plot.regions_pco() for plotting PCO axes

Examples

# Load dataset; vertebral index in first column
# ('Vertebra' column)
data("dolphin")

# Compute PC scores with prcomp:
PCA <- prcomp(dolphin[-1], scale = TRUE)

# Extract PC scores and eigenvalues:
PCA_scores <- as.data.frame(PCA$x)
PCA_eigenval <- PCA$sdev^2


# Process PC scores and morphological data:
pco_dolphin <- process_PC(data = dolphin,
                          pos = "Vertebra",
                          pcscores = PCA_scores,
                          eigenvals = PCA_eigenval,
                          posPC = dolphin[[1]])