HarmonyIntegration | R Documentation |
Harmony Integration
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,
...
)
object |
An |
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 |
...
This function requires the harmony package to be installed
harmony::HarmonyMatrix()
## 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)
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