harmony (version 1.2.1)

RunHarmony: Generic function that runs the harmony algorithm on single-cell genomics cell embeddings.

Description

RunHarmony is generic function that runs the main Harmony algorithm. If working with single cell R objects, please refer to the documentation of the appropriate generic API: (RunHarmony.Seurat() or RunHarmony.SingleCellExperiment()). If users work with other forms of cell embeddings, the can pass them directly to harmony using RunHarmony.default() API. All the function arguments listed here are common in all RunHarmony interfaces.

Usage

RunHarmony(...)

Value

If used with single-cell objects, it will return the updated single-sell object. For standalone operation, it returns the corrected cell embeddings or the R6 harmony object (see RunHarmony.default()).

Arguments

...

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.

verbose

Whether to print progress messages. TRUE to print, FALSE to suppress.

.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.SingleCellExperiment(), RunHarmony.default()