checkArgs {scPCA}R Documentation

Check Arguments passed to the scPCA Function

Description

Checks whether or not the all arguments in the scPCA functions are input properly.

Usage

checkArgs(
  target,
  background,
  center,
  scale,
  n_eigen,
  contrasts,
  penalties,
  clust_method,
  linkage_method
)

Arguments

target

The target (experimental) data set, in a standard format such as a data.frame or matrix.

background

The background data set, in a standard format such as a data.frame or matrix.

center

A logical indicating whether the target and background data sets should be centered to mean zero.

scale

A logical indicating whether the target and background data sets should be scaled to unit variance.

n_eigen

A numeric indicating the number of eigenvectors to be computed.

contrasts

A numeric vector of the contrastive parameters.

penalties

A numeric vector of the penalty terms.

clust_method

A character specifying the clustering method to use for choosing the optimal constrastive parameter. Currently, this is limited to either k-means, partitioning around medoids (PAM), and hierarchical clustering. The default is k-means clustering.

linkage_method

A character specifying the agglomerative linkage method to be used if clust_method = "hclust". The options are ward.D2, single, complete, average, mcquitty, median, and centroid. The default is complete.

Value

Whether all argument conditions are satisfied


[Package scPCA version 1.2.0 Index]