Constructor for SCENIC parameters

Usage

params_scenic(
  min_counts = 50L,
  min_cells = 0.03,
  learner_type = "randomforest",
  gene_batch_strategy = "correlated",
  gene_batch_size = NULL,
  n_pcs = 50L,
  n_subsample = 100000L,
  learner_params = list()
)

Arguments

min_counts: Integer. Minimum total counts a gene needs to be included in the analysis. Defaults to 50L.
min_cells: Numeric. Minimum proportion of cells (between 0 and 1) that must express a gene for it to be considered. Defaults to 0.03.
learner_type: Character. Regression learner to use. One of "randomforest", "extratrees", or "grnboost2". Defaults to "randomforest".
gene_batch_strategy: Character. Strategy for grouping target genes into batches. One of "random" or "correlated". Only used for "randomforest" and "extratrees" learners; ignored for "grnboost2". Defaults to "correlated".
gene_batch_size: Optional integer. Number of genes per batch. If NULL (default), the batch size is determined automatically. Ignored for "grnboost2".
n_pcs: Integer. Number of PCs to use for the correlated gene batch strategy. Defaults to 50L.
n_subsample: Integer. Cell subsampling threshold for the correlated gene batch strategy. If the number of cells meets or exceeds this value, n_subsample cells are randomly selected prior to running randomised SVD. Defaults to 100000L.
learner_params: List. Optional overrides for the regression learner parameters. For "randomforest", see params_scenic_random_forest_defaults(). For "extratrees", see params_scenic_extra_trees_defaults(). For "grnboost2", see params_scenic_gradient_boosting_defaults().

Value

A named flat list with all SCENIC parameters.