Run dimensionality reduction

Usage

RunDimReduction(
  srt,
  prefix = "",
  features = NULL,
  assay = NULL,
  layer = "data",
  linear_reduction = NULL,
  linear_reduction_dims = 50,
  linear_reduction_params = list(),
  force_linear_reduction = FALSE,
  nonlinear_reduction = NULL,
  nonlinear_reduction_dims = 2,
  reduction_use = NULL,
  reduction_dims = NULL,
  graph_use = NULL,
  neighbor_use = NULL,
  nonlinear_reduction_params = list(),
  force_nonlinear_reduction = TRUE,
  verbose = TRUE,
  seed = 11
)

Arguments

srt: A Seurat object.
prefix: The prefix used to name the result.
features: Use features expression data to run linear or nonlinear dimensionality reduction.
assay: Specific assay to get data from.
layer: Specific layer to get data from.
linear_reduction: Method of linear dimensionality reduction. Options are "pca", "ica", "nmf", "mds", "glmpca".
linear_reduction_dims: Total number of dimensions to compute and store for linear_reduction.
linear_reduction_params: Other parameters passed to the linear_reduction method.
force_linear_reduction: Whether force to do linear dimensionality reduction.
nonlinear_reduction: Method of nonlinear dimensionality reduction. Options are "umap", "umap-naive", "tsne", "dm", "phate", "pacmap", "trimap", "largevis".
nonlinear_reduction_dims: Total number of dimensions to compute and store for nonlinear_reduction.
reduction_use: Which dimensional reduction to use as input for nonlinear_reduction.
reduction_dims: Which dimensions to use as input for nonlinear_reduction, used only if features is NULL.
graph_use: Name of graph to use for the nonlinear_reduction.
neighbor_use: Name of neighbor to use for the nonlinear_reduction.
nonlinear_reduction_params: Other parameters passed to the nonlinear_reduction method.
force_nonlinear_reduction: Whether force to do nonlinear dimensionality reduction.
verbose: Whether to print the message. Default is TRUE.
seed: Set a seed. Default is 11.