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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.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.

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.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)
#>  [2026-01-27 08:16:35] Start standard scop workflow...
#>  [2026-01-27 08:16:35] Checking a list of <Seurat>...
#> ! [2026-01-27 08:16:35] Data 1/1 of the `srt_list` is "unknown"
#>  [2026-01-27 08:16:35] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 1/1 of the `srt_list`...
#>  [2026-01-27 08:16:38] Perform `Seurat::FindVariableFeatures()` on the data 1/1 of the `srt_list`...
#>  [2026-01-27 08:16:38] Use the separate HVF from srt_list
#>  [2026-01-27 08:16:38] Number of available HVF: 2000
#>  [2026-01-27 08:16:39] Finished check
#>  [2026-01-27 08:16:39] Perform `Seurat::ScaleData()`
#>  [2026-01-27 08:16:39] Perform pca linear dimension reduction
#>  [2026-01-27 08:16:41] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#>  [2026-01-27 08:16:41] Reorder clusters...
#>  [2026-01-27 08:16:41] Perform umap nonlinear dimension reduction
#>  [2026-01-27 08:16:41] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#>  [2026-01-27 08:16:46] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#>  [2026-01-27 08:16:51] Run scop standard workflow completed
panc8_sub <- RunHarmony2(
  panc8_sub,
  group.by.vars = "tech",
  reduction = "pca"
)
#> Transposing data matrix
#> Initializing state using k-means centroids initialization
#> Harmony 1/10
#> Harmony 2/10
#> Harmony 3/10
#> Harmony 4/10
#> Harmony 5/10
#> Harmony 6/10
#> Harmony 7/10
#> Harmony converged after 7 iterations

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"
)
#>  [2026-01-27 08:17:02] Start standard scop workflow...
#>  [2026-01-27 08:17:02] Checking a list of <Seurat>...
#>  [2026-01-27 08:17:03] Data 1/1 of the `srt_list` has been log-normalized
#>  [2026-01-27 08:17:03] Perform `Seurat::FindVariableFeatures()` on the data 1/1 of the `srt_list`...
#>  [2026-01-27 08:17:03] Use the separate HVF from srt_list
#>  [2026-01-27 08:17:03] Number of available HVF: 2000
#>  [2026-01-27 08:17:04] Finished check
#>  [2026-01-27 08:17:04] Perform `Seurat::ScaleData()`
#>  [2026-01-27 08:17:04] Perform Harmony linear dimension reduction
#>  [2026-01-27 08:17:04] `linear_reduction` Harmony is already existed. Skip calculation
#>  [2026-01-27 08:17:05] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#>  [2026-01-27 08:17:05] Reorder clusters...
#>  [2026-01-27 08:17:05] Perform umap nonlinear dimension reduction
#>  [2026-01-27 08:17:05] Non-linear dimensionality reduction (umap) using (HarmonyHarmony) dims (1-30) as input
#>  [2026-01-27 08:17:10] Non-linear dimensionality reduction (umap) using (HarmonyHarmony) dims (1-30) as input
#>  [2026-01-27 08:17:15] Run scop standard workflow completed

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


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