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Plot a ComplexHeatmap.

Source: R/plot_heatmap.R
plot_heatmap.Rd

This function takes an arbitrary dataset as an input and returns a ComplexHeatmap plot of samples based on similarity of microbial abundances. The function takes arguments listed here as well as any others to be passed on to ComplexHeatmap::Heatmap(). Note, the "circlize" and "ComplexHeatmap" packages are required to use this function.

Usage

plot_heatmap(
  inputData,
  annotationData = NULL,
  plot_title = NULL,
  name = "Input data",
  plottingColNames,
  annotationColNames = NULL,
  colList = list(),
  scale = FALSE,
  showColumnNames = TRUE,
  showRowNames = TRUE,
  colorSets = c("Set1", "Set2", "Set3", "Pastel1", "Pastel2", "Accent", "Dark2",
    "Paired"),
  choose_color = c("blue", "gray95", "red"),
  split_heatmap = "none",
  annotationplotting = NULL,
  column_order = NULL,
  ...
)

Arguments

inputData

an input data object. It should either be of the class SummarizedExperiment and contain the data and annotation data as columns in the colData, or alternatively be of the classes data.frame or matrix and contain only the plotting data. Required.

annotationData

a data.frame or matrix of annotation data, with one column. Only required if inputData is a data.frame or matrix of plotting data. The row names must equal those of the inputData column names. Default is NULL.

plot_title

a character string with the plot title of the heatmap. The default is NULL.

name

a character string with the name of the data to be displayed. Default is "Input data".

plottingColNames

a vector of the column names in colData that contain the plotting data. Only required if inputData is a SummarizedExperiment object.

annotationColNames

a vector of the column names in colData that contain the annotation data. Only required if inputData is a SummarizedExperiment. Default is NULL.

colList

a named list of named vectors specifying custom color information to pass to ComplexHeatmap::Heatmap(). The list should have as many elements as there are annotation columns, and each element name should correspond exactly with the name of each annotation column. The colors in the vector elements should be named according to the levels of the factor in that column's annotation data if the annotation is discrete, or it should be produced with circlize::colorRamp2 if the annotation is continuous. By default, ColorBrewer color sets will be used. See the the parameter colorSets for additional details.

scale

logical. Setting scale = TRUE scales the plotting data. The default is FALSE.

showColumnNames

logical. Setting showColumnNames = TRUE will show the column names (i.e. sample names) on the heatmap. The default is TRUE.

showRowNames

logical. Setting showColumnNames = TRUE will show the row names (i.e. plotting names) on the heatmap. The default is TRUE.

colorSets

a vector of names listing the color sets in the order that they should be used in creating the heatmap. By default, this function will use the color sets in the order listed in Usage for annotation information. You may replace the default with the same collection of sets in order that you want to use them, or provide custom color sets with the colList parameter.

choose_color

a vector of color names to be interpolated for the heatmap gradient, or a colorRamp function produced by circlize::colorRamp2. The default is c("blue", "gray95", "red").

split_heatmap

a character string either giving the column title of annotationplotting containing annotation data for which to split the heatmap rows, or "none" if no split is desired.

annotationplotting

a data.frame or matrix with information to be used in splitting the heatmap. The first column should plotting names. The column of annotation information should be specified in split_heatmap. Other columns will be ignored. The default is sigAnnotData.

column_order

a vector of character strings indicating the order in which to manually arrange the heatmap columns. Default is NULL, such that column order is automatically determined via clustering.

...

Additional arguments to be passed to ComplexHeatmap::Heatmap().

Value

A ComplexHeatmap plot.

Details

If both annotationData = NULL and annotationColNames = NULL, no annotation bar will be drawn on the heatmap.

Code was adapted from the TBSignatureprofiler R package.

Author

David Jenkins, Aubrey Odom

Examples

library(SummarizedExperiment)
#> Loading required package: MatrixGenerics
#> Loading required package: matrixStats
#> 
#> Attaching package: ‘MatrixGenerics’
#> The following objects are masked from ‘package:matrixStats’:
#> 
#>     colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
#>     colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
#>     colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
#>     colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
#>     colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
#>     colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
#>     colWeightedMeans, colWeightedMedians, colWeightedSds,
#>     colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
#>     rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
#>     rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
#>     rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
#>     rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
#>     rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
#>     rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
#>     rowWeightedSds, rowWeightedVars
#> Loading required package: GenomicRanges
#> Loading required package: stats4
#> Loading required package: BiocGenerics
#> 
#> Attaching package: ‘BiocGenerics’
#> The following objects are masked from ‘package:stats’:
#> 
#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from ‘package:base’:
#> 
#>     Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#>     as.data.frame, basename, cbind, colnames, dirname, do.call,
#>     duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
#>     lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
#>     pmin.int, rank, rbind, rownames, sapply, setdiff, table, tapply,
#>     union, unique, unsplit, which.max, which.min
#> Loading required package: S4Vectors
#> 
#> Attaching package: ‘S4Vectors’
#> The following object is masked from ‘package:utils’:
#> 
#>     findMatches
#> The following objects are masked from ‘package:base’:
#> 
#>     I, expand.grid, unname
#> Loading required package: IRanges
#> Loading required package: GenomeInfoDb
#> Loading required package: Biobase
#> Welcome to Bioconductor
#> 
#>     Vignettes contain introductory material; view with
#>     'browseVignettes()'. To cite Bioconductor, see
#>     'citation("Biobase")', and for packages 'citation("pkgname")'.
#> 
#> Attaching package: ‘Biobase’
#> The following object is masked from ‘package:MatrixGenerics’:
#> 
#>     rowMedians
#> The following objects are masked from ‘package:matrixStats’:
#> 
#>     anyMissing, rowMedians
# Example with a Summarized Experiment data object
dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") |> readRDS()
input_SE <- dat[["MicrobeGenetics"]]

## Creating a continuous color ramp annot col list
Hairrange <- range(colData(input_SE)[, "HairLength"])
color2 <- circlize::colorRamp2(c(Hairrange[1], Hairrange[2]), c("blue", "red"))
color.list <- list("HairLength" = color2)

## Create plot
plot_heatmap(
  inputData = input_SE,
  name = "Microbe abundances",
  plot_title = "Example Heatmap",
  plottingColNames = colnames(input_SE),
  annotationColNames = "HairLength",
  colList = color.list,
  scale = TRUE,
  showColumnNames = TRUE,
  showRowNames = FALSE,
  colorSets = 
    c("Set1", "Set2", "Set3", "Pastel1", "Pastel2", "Accent", "Dark2",
      "Paired"),
  choose_color = c("blue", "gray95", "red"),
  split_heatmap = "none",
  column_order = NULL
)

#> NULL

# Artificial data example - matrix input
mat_testdata <- rbind(matrix(c(rnorm(80), rnorm(80) + 5), 16, 10,
                             dimnames = list(paste0("Taxon", seq_len(16)),
                                             paste0("sample", seq_len(10)))),
                      matrix(rnorm(1000), 100, 10,
                             dimnames = list(paste0("Taxon0", seq_len(100)),
                                             paste0("sample", seq_len(10)))))
cov_mat <- data.frame(sample = c(rep("down", 5), rep("up", 5))) |>
  magrittr::set_rownames(paste0("sample", seq_len(10)))

# Example using custom colors for the annotation information
color2 <- stats::setNames(c("purple", "black"), c("down", "up"))
color.list <- list("sample" = color2)

plot_heatmap(
  inputData = mat_testdata,
  annotationData = cov_mat,
  name = "Data",
  plot_title = "Example",
  plottingColNames = NULL,
  annotationColNames = NULL,
  colList = color.list,
  scale = FALSE,
  showColumnNames = TRUE,
  showRowNames = FALSE,
  colorSets = c("Set1", "Set2", "Set3", "Pastel1", "Pastel2", "Accent", "Dark2",
                "Paired"),
  choose_color = c("blue", "gray95", "red"),
  split_heatmap = "none",
  column_order = NULL
)

#> NULL