HarmonyIntegration: Harmony Integration

In Seurat: Tools for Single Cell Genomics

Harmony Integration

Description

Harmony Integration

Usage

HarmonyIntegration(
  object,
  orig,
  features = NULL,
  scale.layer = "scale.data",
  new.reduction = "harmony",
  layers = NULL,
  npcs = 50L,
  key = "harmony_",
  theta = NULL,
  lambda = NULL,
  sigma = 0.1,
  nclust = NULL,
  tau = 0,
  block.size = 0.05,
  max.iter.harmony = 10L,
  max.iter.cluster = 20L,
  epsilon.cluster = 1e-05,
  epsilon.harmony = 1e-04,
  verbose = TRUE,
  ...
)

Arguments

object	An Assay5 object
orig	A dimensional reduction to correct
features	Ignored
scale.layer	Ignored
new.reduction	Name of new integrated dimensional reduction
layers	Ignored
npcs	If doing PCA on input matrix, number of PCs to compute
key	Key for Harmony dimensional reduction
theta	Diversity clustering penalty parameter
lambda	Ridge regression penalty parameter
sigma	Width of soft kmeans clusters
nclust	Number of clusters in model
tau	Protection against overclustering small datasets with large ones
block.size	What proportion of cells to update during clustering
max.iter.harmony	Maximum number of rounds to run Harmony
max.iter.cluster	Maximum number of rounds to run clustering at each round of Harmony
epsilon.cluster	Convergence tolerance for clustering round of Harmony
epsilon.harmony	Convergence tolerance for Harmony
verbose	Whether to print progress messages. TRUE to print, FALSE to suppress
...	Ignored

Value

...

Note

This function requires the harmony package to be installed

See Also

harmony::HarmonyMatrix()

Examples

## Not run: 
# Preprocessing
obj <- SeuratData::LoadData("pbmcsca")
obj[["RNA"]] <- split(obj[["RNA"]], f = obj$Method)
obj <- NormalizeData(obj)
obj <- FindVariableFeatures(obj)
obj <- ScaleData(obj)
obj <- RunPCA(obj)

# After preprocessing, we integrate layers with added parameters specific to Harmony:
obj <- IntegrateLayers(object = obj, method = HarmonyIntegration, orig.reduction = "pca",
  new.reduction = 'harmony', verbose = FALSE)

# Modifying Parameters
# We can also add arguments specific to Harmony such as theta, to give more diverse clusters
obj <- IntegrateLayers(object = obj, method = HarmonyIntegration, orig.reduction = "pca",
  new.reduction = 'harmony', verbose = FALSE, theta = 3)
# Integrating SCTransformed data
obj <- SCTransform(object = obj)
obj <- IntegrateLayers(object = obj, method = HarmonyIntegration,
  orig.reduction = "pca", new.reduction = 'harmony',
  assay = "SCT", verbose = FALSE)

## End(Not run)

Seurat documentation built on May 29, 2024, 4:20 a.m.