harmony (version 2.0.5)

harmony_options: Set advanced parameters for RunHarmony

Description

Set advanced parameters for RunHarmony

Usage

harmony_options(
  alpha = 0.2,
  tau = 0,
  block.size = 0.05,
  max.iter.cluster = 4,
  epsilon.cluster = 0.001,
  epsilon.harmony = 0.01,
  batch.prop.cutoff = 1e-05
)

Value

Return a list for `.options` argument of `RunHarmony`

Arguments

alpha

When setting lambda = NULL and use lambda estimation mode, lambda would be determined by the expected number of cells assuming idependece between batches and clusters. i.e., lambda = alpha * expected number of cells, default 0.2 and alpha should be 0 < alpha < 1

tau

Protection against overclustering small datasets with large ones. `tau` is the expected number of cells per cluster.

block.size

What proportion of cells to update during clustering. Between 0 to 1, default 0.05. Larger values may be faster but less accurate.

max.iter.cluster

Maximum number of rounds to run clustering at each round of Harmony.

epsilon.cluster

Convergence tolerance for clustering round of Harmony. Set to -Inf to never stop early.

epsilon.harmony

Convergence tolerance for Harmony. Set to -Inf to never stop early. When `epsilon.harmony` is set to not NULL, then user-supplied values of `early_stop` is ignored.

batch.prop.cutoff

During the integration step, if a batch has less of the specified proportion in a harmony cluster it will be excluded from the integration step. For example, batch.prop.cutoff=0.01 and a batch has less than 1/100 of its cells soft-assigned to a cluster this batch won't participating in the correction step for the particular batch.

Examples

## If want to set max.iter.cluster to be 100, do
if (FALSE) {
RunHarmony(data_meta, meta_data, vars_use,
              .options = harmony_options(max.iter.cluster = 100))
}