Run Harmony algorithm

This is a modified version of harmony::RunHarmony specifically designed for compatibility with RunSymphonyMap.

Usage

RunHarmony2(object, ...)

# S3 method for class 'Seurat'
RunHarmony2(
  object,
  group.by.vars,
  assay = NULL,
  reduction = "pca",
  dims.use = 1:30,
  project.dim = TRUE,
  reduction.name = "Harmony",
  reduction.save = NULL,
  reduction.key = "Harmony_",
  verbose = TRUE,
  seed.use = 11,
  ...
)

Arguments

object

A Seurat object.

...

Additional arguments to be passed to harmony::RunHarmony.

group.by.vars

The batch variable name.

assay

Which assay to use. If NULL, the default assay of the Seurat object will be used. When the object also contains ChromatinAssay, the default assay and additional ChromatinAssay will be preprocessed sequentially.

reduction

Which dimensionality reduction to use. Default is "pca".

dims.use

The dimensions to be used. Default is 1:30.

project.dim

Whether to project dimension reduction loadings. Default is TRUE.

reduction.name

The name of the reduction to be stored in the Seurat object. Default is "Harmony".

reduction.save

Deprecated alias for reduction.name, retained for compatibility with harmony::RunHarmony.Seurat.

reduction.key

The prefix for the column names of the Harmony embeddings. Default is "Harmony_".

verbose

Whether to print the message. Default is TRUE.

seed.use

Random seed for reproducibility. Default is 11.

Examples

data(panc8_sub)
panc8_sub <- standard_scop(panc8_sub)
#> ℹ [2026-05-14 07:27:14] Start standard processing workflow...
#> ℹ [2026-05-14 07:27:14] Checking a list of <Seurat>...
#> ! [2026-05-14 07:27:15] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-05-14 07:27:15] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on 1/1 of `srt_list`...
#> ℹ [2026-05-14 07:27:17] Perform `Seurat::FindVariableFeatures()` on 1/1 of `srt_list`...
#> ℹ [2026-05-14 07:27:17] Use the separate HVF from `srt_list`
#> ℹ [2026-05-14 07:27:17] Number of available HVF: 2000
#> ℹ [2026-05-14 07:27:18] Finished check
#> ℹ [2026-05-14 07:27:18] Perform `Seurat::ScaleData()`
#> ℹ [2026-05-14 07:27:18] Perform pca linear dimension reduction
#> ℹ [2026-05-14 07:27:19] Use stored estimated dimensions 1:20 for Standardpca
#> ℹ [2026-05-14 07:27:19] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-05-14 07:27:19] Reorder clusters...
#> ℹ [2026-05-14 07:27:19] Skip `log1p()` because `layer = data` is not "counts"
#> ℹ [2026-05-14 07:27:20] Perform umap nonlinear dimension reduction
#> ℹ [2026-05-14 07:27:20] Perform umap nonlinear dimension reduction using Standardpca (1:20)
#> ℹ [2026-05-14 07:27:26] Perform umap nonlinear dimension reduction using Standardpca (1:20)
#> ✔ [2026-05-14 07:27:32] Standard processing workflow completed
panc8_sub <- RunHarmony2(
  panc8_sub,
  group.by.vars = "tech",
  reduction = "pca"
)
#> Transposing data matrix
#> Using automatic lambda estimation
#> Thetas: 2
#> Initializing state using k-means centroids initialization
#> Initializing centroids
#> Harmony 1/10
#> Harmony 2/10
#> Harmony 3/10
#> Harmony 4/10
#> Harmony 5/10
#> Harmony 6/10
#> Harmony 7/10
#> Harmony 8/10
#> Harmony 9/10
#> Harmony converged after 9 iterations
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 't': ‘Z_corr’ is not a valid field or method name for reference class “Rcpp_harmony”

CellDimPlot(
  panc8_sub,
  group.by = c("tech", "celltype"),
  reduction = "pca"
)


CellDimPlot(
  panc8_sub,
  group.by = c("tech", "celltype"),
  reduction = "Harmony"
)


panc8_sub <- standard_scop(
  panc8_sub,
  prefix = "Harmony",
  linear_reduction = "Harmony"
)
#> ℹ [2026-05-14 07:27:34] Start standard processing workflow...
#> Error in standard_scop(panc8_sub, prefix = "Harmony", linear_reduction = "Harmony"): `linear_reduction` must be one of: "pca", "svd", "ica", "nmf", "mds",
#> and "glmpca"

CellDimPlot(
  panc8_sub,
  group.by = c("tech", "celltype"),
  reduction = "StandardpcaUMAP2D"
)


CellDimPlot(
  panc8_sub,
  group.by = c("tech", "celltype"),
  reduction = "HarmonyUMAP2D"
)