Calculate_padjMFC: Calculate_padjMFC

In stefanavey/titer: Tools for analyzing and visualizing antibody titer data

Calculate_padjMFC

Description

Calculate_padjMFC calculates the paired, adjusted maximum fold change (padjMFC)

Usage

Calculate_padjMFC(
  dat,
  fcCol = "fc_norm_max_ivt",
  d0Col = "d0_norm_paired",
  discretize = c(0.2, 0.3),
  scaleResiduals = FALSE,
  responseLabels = paste0(c("low", "moderate", "high"), "Responder"),
  ...
)

Arguments

dat	the data containing the columns fcCol and d0Col
fcCol	character string specifying the name of the fold change column from dat
d0Col	character string specifying the name of the day 0 column from dat
discretize	a vector of quantiles in (0, 0.5] specifying where to make the cutoff for low, moderate and high responses. Default is 20% and 30%.
scaleResiduals	Logical. Should residuals be scaled inversely by the square of the confidence intervals from the linear model.
responseLabels	names for low, moderate and high responses
...	Additional arguments passed to lm

Details

Calculate the paired, adjusted maximum fold change (padjMFC) from fc_norm_max_ivt and d0_norm_paired using linear regression to remove the effect of baseline titers. Missing (NA) values are handled and any missing values in fcCol and d0Col will also be missing in the output.

Value

A list with the first element named "linearModel" for the linear model and then "padjMFC" containing the continuous padjMFC metric and one additional element for each value of discretize giving the discrete labels.

Author(s)

Stefan Avey

See Also

lm

Examples

## First Example

stefanavey/titer documentation built on Jan. 27, 2023, 3:41 a.m.