normalizeMoltenData: Normalize data

In nbenn/singleCellFeatures: Analyze single cell features stored in an openBIS instance

Description

Given two well level matrices combined by prepareDataforGlm, normalize the data.

Usage

normalizeMoltenData(data, features = "all", method = "zScore",
  separate.wells = FALSE)

Arguments

data	The data frame holding the data to be normalized.
features	A regular expression specifying the features to be normalized. The string "all" includes all available.
method	A string specifying the normalization method to be used. The following are implemented: unitInterval, scaleRange, center, unitVar, zScore.
separate.wells	Are the two wells to be treated seperately or concurrently?

Value

A data.frame holding normalized data.

Examples

wells     <- findWells(plates="J107-2C", well.names=c("H2", "H6"))
data      <- unlist(getSingleCellData(wells), recursive=FALSE)
cleaned   <- lapply(data, cleanData, "lower")
melted    <- lapply(cleaned, meltData)
data.mint <- prepareDataforGlm(melted[[2]]$mat$Cells, 
                               melted[[1]]$mat$Cells, test=NULL)$train
data.scal <- normalizeMoltenData(data.mint, features="intensity",
                                 method="unitInterval")

nbenn/singleCellFeatures documentation built on May 23, 2019, 12:24 p.m.