normaliseCountMatrix: normaliseCountMatrix

In PolinaPavlovich/CONCLUS: ScRNA-seq workflow CONCLUS - from CONsensus CLUSters to a meaningful CONCLUSion.

Description

Create a SingleCellExperiment object and perform normalization. The same as conclus::normalizeCountMatrix.

Usage

normaliseCountMatrix(countMatrix, species, method = "default",
  sizes = c(20, 40, 60, 80, 100), rowData = NULL, colData = NULL,
  alreadyCellFiltered = FALSE, runQuickCluster = TRUE,
  databaseDir = system.file("extdata", package = "conclus"))

Arguments

countMatrix	a matrix with non-normalised gene expression.
species	either 'mmu' or 'human'.
method	a method of clustering: available option is "default" using scran and scater.
sizes	a vector of size factors from scran::computeSumFactors() function.
rowData	a data frame with information about genes
colData	a data frame with information about cells
alreadyCellFiltered	if TRUE, cells quality check and filtering will not be applied. However, the function may delete some cells if they have negative size factors after scran::computeSumFactors.
runQuickCluster	if scran::quickCluster() function must be applied. Usually, it allows to improve normalization for medium-size count matrices. However, it is not recommended for datasets with less than 200 cells and may take too long for datasets with more than 10000 cells.
databaseDir	a path to annotation database provided with CONCLUS called "Mmus_gene_database_secretedMol.tsv" (only for MusMusculus 'mmu'). The function will work also without the database but slower because it will retrieve genes info from biomaRt.

Value

A SingleCellExperiment object with normalized gene expression, colData, and rowData.

PolinaPavlovich/CONCLUS documentation built on May 10, 2019, 2:42 p.m.