% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/epiMap.R
\name{epiMap}
\alias{epiMap}
\title{Make Pheatmap from Comparison Matrix}
\usage{
epiMap(compare.matrix, value, annotate,
  clustering_distance_rows = "euclidean",
  clustering_distance_cols = "euclidean",
  clustering_method = "complete", annotate.colors = NA,
  color = colorRampPalette(c("blue", "white", "red"))(1000),
  loci.percent = 0.1, show.rows = FALSE, show.columns = FALSE,
  font.size = 6, pdf.height = 10, pdf.width = 10, sve = FALSE, ...)
}
\arguments{
\item{compare.matrix}{The comparison matrix generated from
the compMatrix() function}

\item{value}{The value to be graphed in the pheatmap.
Possible values are 'read', 'pdr', 'meth', 'epipoly',
and 'shannon'.}

\item{annotate}{A dataframe containing the annotation information
for the columns of the pheatmap. The row names must be the names
of the samples. The columns (any number) are the annotations. E.g. a column
called 'TET2' with factors 'Pos' and 'Neg' for each sample that
is positive or negative for the TET2 gene}

\item{clustering_distance_rows}{Distance measure used in clustering rows.}

\item{clustering_distance_cols}{Distance measure used in clustering columns.}

\item{clustering_method}{clustering method used.}

\item{annotate.colors}{A list containing the colors for the
annotation information. Each element in the list is a vector
of colors with names that correspond to the columns of 'annotate'.}

\item{color}{a vector of colors used in heatmap.}

\item{loci.percent}{The top percentage of loci, as a decimal,
to be displayed on the pheatmap based on standard deviation,
e.g. a value of 0.20 is equivalent to the top 20\% of loci
(default: 0.10)}

\item{show.rows}{A boolean stating if the row names should be
displayed on the pheatmap (default: FALSE)}

\item{show.columns}{A boolean stating if the column names should
be displayed on the pheatmap (default: FALSE)}

\item{font.size}{An integer representing the font size to be used
for the pheatmap labels (default: 6)}

\item{pdf.height}{An integer representing the height (in inches)
of the pdf file for the pheatmap (default: 10)}

\item{pdf.width}{An integer representing the width (in inches)
of the pdf file for the pheatmap (default: 10)}

\item{sve}{A boolean to save the plot (default: FALSE)}

\item{...}{any arguments in the function pheatmap()}
}
\value{
A pheatmap object that contains the tree data for
both rows and columns and the final pheatmap plot
}
\description{
Creates a pheatmap for the top 'loci.percent' of values
of max standard deviation from the comparison matrix
generated by compMatrix(). The rows represent the loci
of the epiallele and the columns represent the sample
names. The columns can be annotated by adding annotation
information as a parameter.
}
\examples{
comp.Matrix<-data.frame(
p1=c(0.6,0.3,0.5,0.5,0.5,0.6,0.45,0.57,0.45,0.63,0.58,0.67,0.5,0.42,0.67),
p2=c(0.62,0.63,0.55,0.75,0.84,0.58,1,0.33,1,0.97,0.57,0.68,0.73,0.72,0.82),
p3=c(0.72,0.53,0.62,0.69,0.37,0.85,1,0.63,0.87,0.87,0.82,0.81,0.79,
0.62,0.68),
N1=c(0.15,0.24,0.15,0.26,0.34,0.32,0.23,0.14,0.26,0.32,0.12,0.16,0.31,
0.24,0.32),
N2=c(0.32,0.26,0.16,0.36,0.25,0.37,0.12,0.16,0.41,0.47,0.13,0.52,0.42,
0.41,0.23),
N3=c(0.21,0.16,0.32,0.16,0.36,0.27,0.24,0.26,0.11,0.27,0.39,0.5,0.4,
0.31,0.33),
type=rep(c("pdr","epipoly","shannon"),c(5,5,5)),
location=rep(c("chr22-327:350:361:364","chr22-755:761:771:773",
"chr22-761:771:773:781","chr22-821:837:844:849","chr22-838:845:850:858"),
3),stringsAsFactors =FALSE )

subtype <- data.frame(Type= c(rep('CEBPA_sil', 3), rep('Normal', 3)),
row.names = colnames(comp.Matrix)[1:6],stringsAsFactors = FALSE)

pmap <- epiMap(compare.matrix = comp.Matrix,
value = 'epipoly',annotate = subtype,
clustering_distance_rows = "euclidean",
clustering_distance_cols = "euclidean",
clustering_method = "complete",annotate.colors = NA,
color= colorRampPalette(c("blue","white","red"))(1000),
loci.percent = 1, show.rows = FALSE,
show.columns = TRUE, font.size = 15,
pdf.height = 10, pdf.width = 10, sve = TRUE)
}