harmony (version 1.2.1)

RunHarmony.SingleCellExperiment: Applies harmony on PCA cell embeddings of a SingleCellExperiment.

Description

Applies harmony on PCA cell embeddings of a SingleCellExperiment.

Usage

# S3 method for SingleCellExperiment
RunHarmony(
  object,
  group.by.vars,
  dims.use = NULL,
  verbose = TRUE,
  reduction.save = "HARMONY",
  ...
)

Value

SingleCellExperiment object. After running RunHarmony, the corrected cell embeddings can be accessed with reducedDim(object, "Harmony").

Arguments

object

SingleCellExperiment with the PCA reducedDim cell embeddings populated

group.by.vars

the name(s) of covariates that harmony will remove its effect on the data.

dims.use

a vector of indices that allows only selected cell embeddings features to be used.

verbose

enable verbosity

reduction.save

the name of the new slot that is going to be created by harmony. By default, HARMONY.

...

Arguments passed on to RunHarmony.default

theta

Diversity clustering penalty parameter. Specify for each variable in vars_use Default theta=2. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.

sigma

Width of soft kmeans clusters. Default sigma=0.1. Sigma scales the distance from a cell to cluster centroids. Larger values of sigma result in cells assigned to more clusters. Smaller values of sigma make soft kmeans cluster approach hard clustering.

lambda

Ridge regression penalty. Default lambda=1. Bigger values protect against over correction. If several covariates are specified, then lambda can also be a vector which needs to be equal length with the number of variables to be corrected. In this scenario, each covariate level group will be assigned the scalars specified by the user. If set to NULL, harmony will start lambda estimation mode to determine lambdas automatically and try to minimize overcorrection (Use with caution still in beta testing).

nclust

Number of clusters in model. nclust=1 equivalent to simple linear regression.

max_iter

Maximum number of rounds to run Harmony. One round of Harmony involves one clustering and one correction step.

early_stop

Enable early stopping for harmony. The harmonization process will stop when the change of objective function between corrections drops below 1e-4

ncores

Number of processors to be used for math operations when optimized BLAS is available. If BLAS is not supporting multithreaded then this option has no effect. By default, ncore=1 which runs as a single-threaded process. Although Harmony supports multiple cores, it is not optimized for multithreading. Increase this number for large datasets iff single-core performance is not adequate.

plot_convergence

Whether to print the convergence plot of the clustering objective function. TRUE to plot, FALSE to suppress. This can be useful for debugging.

.options

Setting advanced parameters of RunHarmony. This must be the result from a call to `harmony_options`. See ?`harmony_options` for parameters not listed above and more details.

See Also

Other RunHarmony: RunHarmony.Seurat(), RunHarmony.default(), RunHarmony()

Examples

if (FALSE) {
## sce is a SingleCellExperiment R object
sce <- RunHarmony(sce, "donor_id")
}