preprocess_cds: Preprocess a cds to prepare for trajectory inference
In scfurl/m3addon: This package adds to the popular "monocle3"

Most analyses (including trajectory inference, and clustering) in Monocle3, require various normalization and preprocessing steps. preprocess_cds executes and stores these preprocessing steps.

Specifically, depending on the options selected, preprocess_cds first normalizes the data by log and size factor to address depth differences, or by size factor only. Next, preprocess_cds calculates a lower dimensional space that will be used as the input for further dimensionality reduction like tSNE and UMAP.

preprocess_cds(
  cds,
  method = c("PCA", "LSI"),
  num_dim = 50,
  norm_method = c("log", "size_only", "none"),
  use_genes = NULL,
  pseudo_count = NULL,
  scaling = TRUE,
  verbose = FALSE,
  ...
)

`cds`	the cell_data_set upon which to perform this operation
`method`	a string specifying the initial dimension method to use, currently either PCA or LSI. For LSI (latent semantic indexing), it converts the (sparse) expression matrix into tf-idf matrix and then performs SVD to decompose the gene expression / cells into certain modules / topics. Default is "PCA".
`num_dim`	the dimensionality of the reduced space.
`norm_method`	Determines how to transform expression values prior to reducing dimensionality. Options are "log", "size_only", and "none". Default is "log". Users should only use "none" if they are confident that their data is already normalized.
`use_genes`	NULL or a list of gene IDs. If a list of gene IDs, only this subset of genes is used for dimensionality reduction. Default is NULL.
`pseudo_count`	NULL or the amount to increase expression values before normalization and dimensionality reduction. If NULL (default), a pseudo_count of 1 is added for log normalization and 0 is added for size factor only normalization.
`scaling`	When this argument is set to TRUE (default), it will scale each gene before running trajectory reconstruction. Relevant for method = PCA only.
`verbose`	Whether to emit verbose output during dimensionality reduction
`...`	additional arguments to pass to limma::lmFit if residual_model_formula is not NULL