scCODA differential abundance

Usage

RunscCODA(
  srt,
  group.by,
  split.by,
  sample.by,
  comparison = NULL,
  reference_cell_type = NULL,
  credible_effect_threshold = 0.95,
  n_mcmc_samples = 20000L,
  envname = "scop_sccoda_env",
  conda = "auto",
  seed = 11,
  verbose = TRUE
)

Arguments

srt: A Seurat object.
group.by: Name of one or more meta.data columns to group (color) cells by.
split.by: Metadata column that identifies the condition groups to compare. For sample-level methods, if split.by is omitted and sample.by is provided, sample.by is treated as the condition column and virtual samples are created within each condition.
sample.by: Metadata column that identifies biological samples. For "milo", "sccoda", and "propeller", when sample.by is omitted or identical to split.by, virtual samples are created within each split.by group for convenience.
comparison: Optional: specify comparisons to perform.
reference_cell_type: Optional reference cell type for scCODA.
credible_effect_threshold: Inclusion probability threshold for credible effects.
n_mcmc_samples: Number of MCMC samples requested in scCODA.
envname: Name of the conda-compatible environment used by scCODA. Defaults to "scop_sccoda_env" to keep the TensorFlow/scCODA stack isolated from the default Python environment.
conda: The path or command name of a conda-compatible executable.
seed: Random seed.
verbose: Whether to print the message. Default is TRUE.

Value

A method result bundle used internally by RunProportionTest.