TestSoftPowersConsensus | R Documentation |
Compute the scale-free topology model fit for different soft power thresholds separately for each input dataset
TestSoftPowersConsensus(
seurat_obj,
powers = c(seq(1, 10, by = 1), seq(12, 30, by = 2)),
use_metacells = TRUE,
networkType = "signed",
corFnc = "bicor",
setDatExpr = FALSE,
group.by = NULL,
group_name = NULL,
multi.group.by = NULL,
multi_groups = NULL,
wgcna_name = NULL,
...
)
seurat_obj |
A Seurat object |
powers |
numeric vector specifying soft powers to test |
use_metacells |
logical flag for whether to use the metacell expression matrix |
networkType |
The type of network to use for network analysis. Options are "signed" (default), "unsigned", or "signed hybrid". This should be consistent with the network chosen for ConstructNetwork |
corFnc |
Correlation function for the gene-gene correlation adjacency matrix. |
setDatExpr |
logical flag indicating whether to run setDatExpr. |
group.by |
A string containing the name of a column in the Seurat object with cell groups (clusters, cell types, etc). If NULL (default), hdWGCNA uses the Seurat Idents as the group. |
group_name |
A string containing a group present in the provided group.by column or in the Seurat Idents. A character vector can be provided to select multiple groups at a time. |
multi.group.by |
A string containing the name of a column in the Seurat object with groups for consensus WGCNA (dataset, sample, condition, etc) |
multi_groups |
A character vecrtor containing the names of groups to select |
... |
additional parameters passed to SetDatExpr |
# TestSoftPowers(pbmc)
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