scDC_noClustering: scDC_noClustering

Description Usage Arguments Value Author(s) Examples

Description

Single-cell Differential Composition Analysis without performing clustering

Usage

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scDC_noClustering(cellTypes = NULL, subject = NULL, calCI = TRUE,
  calCI_method = c("BCa", "multinom", "percentile"), nboot = 10000,
  conf_level = 0.95, ncores = 1, verbose = TRUE)

Arguments

cellTypes

A vector indicates the cell type info of the data

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 BCa, percentile, and multinom.

nboot

Number of bootstrap. If calCI = TRUE, nboot = 10000 by default. Otherwise, nboot = 500.

conf_level

confidence level, with default 0.95

ncores

Number of cores that are used.

verbose

A logical input for whether print the progress.

Value

Returns a data frame.

Author(s)

Yingxin Lin

Examples

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## Loading example data
data("sim", package = "scdney")

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")


## End(Not run)

SydneyBioX/scdney documentation built on Aug. 22, 2019, 10:55 a.m.