--- a
+++ b/man/heatmap_ic.Rd
@@ -0,0 +1,61 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plots.R
+\name{heatmap_ic}
+\alias{heatmap_ic}
+\title{Heatmap for class biotmle}
+\usage{
+heatmap_ic(x, ..., design, FDRcutoff = 0.25, type = c("top", "all"), top = 25)
+}
+\arguments{
+\item{x}{Object of class \code{biotmle} as produced by an appropriate call
+to \code{biomarkertmle}.}
+
+\item{...}{additional arguments passed to \code{superheat::superheat} as
+necessary}
+
+\item{design}{A vector giving the contrast to be displayed in the heatmap.}
+
+\item{FDRcutoff}{Cutoff to be used in controlling the False Discovery Rate.}
+
+\item{type}{A \code{character} describing whether to plot only a top number
+(as defined by FDR-corrected p-value) of biomarkers or all biomarkers.}
+
+\item{top}{Number of identified biomarkers to plot in the heatmap.}
+}
+\value{
+heatmap (from \pkg{superheat}) using hierarchical clustering to plot
+ the changes in the variable importance measure for all subjects across a
+ specified top number of biomarkers.
+}
+\description{
+Heatmap of contributions of a select subset of biomarkers to the variable
+importance measure changes as assessed by influence curve-based estimation,
+across all subjects. The heatmap produced performs supervised clustering, as
+per Pollard & van der Laan (2008) <doi:10.2202/1544-6115.1404>.
+}
+\examples{
+\dontrun{
+library(dplyr)
+library(biotmleData)
+library(SummarizedExperiment)
+data(illuminaData)
+
+colData(illuminaData) <- colData(illuminaData) \%>\%
+  data.frame() \%>\%
+  mutate(age = as.numeric(age > median(age))) \%>\%
+  DataFrame()
+benz_idx <- which(names(colData(illuminaData)) \%in\% "benzene")
+
+biomarkerTMLEout <- biomarkertmle(
+  se = illuminaData,
+  varInt = benz_idx,
+  bppar_type = BiocParallel::SerialParam(),
+  g_lib = c("SL.mean", "SL.glm"),
+  Q_lib = c("SL.mean", "SL.glm")
+)
+
+limmaTMLEout <- modtest_ic(biotmle = biomarkerTMLEout)
+
+heatmap_ic(x = limmaTMLEout, design = design, FDRcutoff = 0.05, top = 10)
+}
+}