RunQuantileAlignSNF | R Documentation |
This is a deprecated function. Call 'RunQuantileNorm' instead.
RunQuantileAlignSNF(
object,
split.by = "orig.ident",
reduction = "iNMF_raw",
reduction.name = "iNMF",
reduction.key = "iNMF_",
recalc.snf = FALSE,
ref_dataset = NULL,
prune.thresh = 0.2,
min_cells = 2,
quantiles = 50,
nstart = 10,
resolution = 1,
center = FALSE,
id.number = NULL,
print.mod = FALSE,
print.align.summary = FALSE,
...
)
object |
A merged Seurat object |
split.by |
Attribute for splitting, defaults to "orig.ident" |
reduction |
Name of reduction to use |
reduction.name |
Name to store resulting DimReduc object as |
reduction.key |
Key for resulting DimReduc |
recalc.snf |
Recalculate |
ref_dataset |
Name of dataset to use as a "reference" for normalization. By default, the dataset with the largest number of cells is used. |
prune.thresh |
Minimum allowed edge weight. Any edges below this are removed (given weight 0) (default 0.2) |
min_cells |
Minimum number of cells to consider a cluster shared across datasets (default 2) |
quantiles |
Number of quantiles to use for quantile normalization (default 50). |
nstart |
Number of times to perform Louvain community detection with different random starts (default 10). |
resolution |
Controls the number of communities detected. Higher resolution -> more communities. (default 1) |
center |
Centers the data when scaling factors (useful for less sparse modalities like methylation data). (default FALSE) |
id.number |
Number to use for identifying edge file (when running in parallel) (generates random value by default). |
print.mod |
Print modularity output from clustering algorithm (default FALSE). |
print.align.summary |
Print summary of clusters which did not align normally (default FALSE). |
... |
Arguments passed to other methods, and to
|
A Seurat object with embeddings from quantileAlignSNF
stored as a DimReduc object with name reduction.name
(key set to reduction.key
)
RunQuantileNorm
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