Description Usage Arguments Value Examples
View source: R/geneADTnetwork.R
A function to visualise the features distribtuion
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | geneADTnetwork(
sce,
RNA_exprs_value = "logcounts",
altExp_name = "ADT",
altExp_exprs_value = "logcounts",
RNA_feature_subset = NULL,
ADT_feature_subset = NULL,
cell_subset = NULL,
cor_threshold = 0.5,
cor_method = c("pearson", "kendall", "spearman"),
RNA_exprs_pct = 0.1,
ADT_exprs_pct = 0.1,
RNA_exprs_threshold = 0,
ADT_exprs_threshold = 0,
network_layout = NULL,
return_igraph = FALSE
)
|
sce |
A singlecellexperiment object |
RNA_exprs_value |
A character indicates which expression value for RNA in assayNames is used. |
altExp_name |
A character indicates which expression matrix is used. by default is none (i.e. RNA). |
altExp_exprs_value |
A character indicates which expression value in assayNames is used. |
RNA_feature_subset |
A vector of characters indicates the subset of features of RNA that are used for visualisation |
ADT_feature_subset |
A vector of characters indicates the subset of features of ADT that are used for visualisation |
cell_subset |
A vector of characters indicates the subset of cells that are used for visualisation |
cor_threshold |
Thresholds of correlation. |
cor_method |
a character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated. |
RNA_exprs_pct |
A numeric indicates the threshold expression percentage of a gene to be considered in correlation analysis |
ADT_exprs_pct |
A numeric indicates the threshold expression percentage of a gene to be considered in correlation analysis |
RNA_exprs_threshold |
A numeric indicates the threshold of RNA expression. By default is 0. |
ADT_exprs_threshold |
A numeric indicates the threshold of ADT expression. By default is 0. |
network_layout |
layout of the network |
return_igraph |
indicates whether return the igraph object |
A igraph object of gene-ADT network
1 2 3 4 5 6 7 8 9 10 11 | library(SingleCellExperiment)
set.seed(2020)
data(sce_control_subset, package = "CiteFuse")
RNA_feature_subset <- sample(rownames(sce_control_subset), 50)
ADT_feature_subset <- rownames(altExp(sce_control_subset, "ADT"))
geneADTnetwork(sce_control_subset,
RNA_feature_subset = RNA_feature_subset,
ADT_feature_subset = ADT_feature_subset,
cor_method = "pearson",
network_layout = igraph::layout_with_fr)
|
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