scDC_noClustering.Rd
Single-cell Differential Composition Analysis without performing clustering
scDC_noClustering(cellTypes = NULL, subject = NULL, calCI = TRUE, calCI_method = c("BCa", "multinom", "percentile"), nboot = 10000, conf_level = 0.95, ncores = 1, verbose = TRUE)
cellTypes | A vector indicates the cell type info of the data |
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subject | A vector indicates the subject info of the data |
calCI | A logical input for whether calculating the confidence interval for proportion |
calCI_method | A string indicates the method that is used to calculate confidence interval. Options include |
nboot | Number of bootstrap. If |
conf_level | confidence level, with default 0.95 |
ncores | Number of cores that are used. |
verbose | A logical input for whether print the progress. |
Returns a data frame.
## Loading example data library(scDC) data("sim") cellTypes = sim$sim_cellTypes subject = sim$sim_subject# NOT RUN { res_noCALCI = scDC_noClustering(cellTypes, subject, calCI = FALSE) res_BCa = scDC_noClustering(cellTypes, subject, calCI = TRUE, calCI_method = "BCa") res_percentile = scDC_noClustering(cellTypes, subject, calCI = TRUE, calCI_method = "percentile") res_multinom = scDC_noClustering(cellTypes, subject, calCI = TRUE, calCI_method = "multinom") # }