rADA (version 1.1.9)

calcScpValues: Calculate screening cut point values for scp()

Description

This function calculates the values needed for the output of the scp() data.frame

Usage

calcScpValues(
  assay.values,
  conf.level = 0.95,
  distrib = c("nonparametric", "normal"),
  transf.method = c("log10", "ln")
)

Arguments

assay.values

List of selected values from the assay data.frame such as selected values from assayMelt()

conf.level

Decimal describing level of confidence to be used for confidence interval calculation. Defaults to 0.95

distrib

Distribution selection to determine the cut point calculation. Two options: 'nonparametric' or 'normal'

transf.method

Transformation method used. The inverse will be calculated as part of the output.

Value

A data.frame cotaining the values: "mean", "sd", "distrib", "cp", "mean.conf.int1", "mean.conf.int2", "cp.conf.int1", "cp.conf.int2"

Examples

# NOT RUN {
assay.df.melted <- assayMelt(assay.df = lognormAssay, exp.name = 'Experiment1')
assay.values <- assay.df.melted[assay.df.melted$DayOperator == 'D1Op1',]$value
#This function assumes that the data has already been transformed.
scp.df <- calcScpValues(assay.values = log10(assay.values), distrib = 'normal',
transf.method = 'log10')



# }