calculate_FalsePositive: Calculate False Positives markers for SingleCellExperiment...

In vallotlab/IDclust: Iterative Differential Clustering for single-cell

Calculate False Positives markers for SingleCellExperiment object

Description

Calculate False Positives markers for SingleCellExperiment object

Usage

calculate_FalsePositive(
  object,
  differential_function = differential_ChromSCape,
  by = "IDcluster",
  logFC.th = log2(1.5),
  qval.th = 0.01,
  nThreads = 1,
  iterations = 5,
  combinatorial.seed = 1,
  ...
)

Arguments

object	A SingleCellExperiment object
differential_function	A function that take in entry a SingleCellExperiment object and parameters passed in ... and returns a data.frame containing the significantly differential features for each cluster.
by	A character specifying the name of the metadata column referencing the clusters.
nThreads	If runFDR==TRUE. An integer specifying of threads to use for the calculation of the FDR.
iterations	An integer specifyung the number of iterations of random subsampling to run.
...	Additional parameters passed to the differential_function. See differential_ChromSCape() for more information on additional parameters for the default function.

Examples

if(requireNamespace("ChromSCape", quietly=TRUE)){
data("scExp", package = "IDclust")
scExp = ChromSCape::find_clusters_louvain_scExp(scExp, resolution = 0.1)
FDR_df = calculate_FalsePositive(scExp, nThreads = 1, iterations = 2)
head(FDR_df)
}

vallotlab/IDclust documentation built on Feb. 16, 2023, 8:58 a.m.