Package 'iheatmapr'

Title: Interactive, Complex Heatmaps
Description: Make complex, interactive heatmaps. 'iheatmapr' includes a modular system for iteratively building up complex heatmaps, as well as the iheatmap() function for making relatively standard heatmaps.
Authors: Alicia Schep [aut] , Sarah Kummerfeld [aut] , Genentech [cph], Andee Kaplan [rev] (Reviewer for rOpensci review process https://github.com/ropensci/onboarding/issues/107), Carl Ganz [rev] (Reviewer for rOpensci review process https://github.com/ropensci/onboarding/issues/107), Alex Johnson [ctb] (plotly.js library), Étienne Tétreault-Pinard [ctb] (plotly.js library), Mikola Lysenko [ctb] (plotly.js library), Ricky Reusser [ctb] (plotly.js library), Robert Monfera [ctb] (plotly.js library), Nicolas Riesco [ctb] (plotly.js library), Miklós Tusz [ctb] (plotly.js library), Chelsea Douglas [ctb] (plotly.js library), Ben Postlethwaite [ctb] (plotly.js library), Chris Parmer [ctb] (plotly.js library), Alex Vados [ctb] (plotly.js library), Plotly [cph] (plotly.js library), Frederick Boehm [ctb] (colorbars & main_heatmap), Alan O'Callaghan [cre]
Maintainer: Alan O'Callaghan <[email protected]>
License: MIT + file LICENSE
Version: 0.7.1
Built: 2024-11-27 03:24:44 UTC
Source: https://github.com/ropensci/iheatmapr

Help Index

add_col_annotation

Description

Adds annotation heatmaps for one or more qualitative or quantitative annotations for each column of a main heatmap.

Usage

## S4 method for signature 'Iheatmap'
add_col_annotation(
  p,
  annotation,
  colors = NULL,
  side = c("top", "bottom"),
  size = 0.05,
  buffer = 0.015,
  inner_buffer = buffer/2,
  layout = list(),
  show_colorbar = TRUE
)

Arguments

p

link{Iheatmap-class} object
annotation

data.frame or object that can be converted to data frame
colors

list of color palettes, with one color per annotation column name
side

side of plot on which to add column annotation
size

relative size of each row annotation
buffer

relative size of buffer between previous subplot and column annotation
inner_buffer

relative size of buffer between each annotation
layout

layout properties for new y axis
show_colorbar

logical indicator to show or hide colorbar

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, add_row_annotation, add_col_signal, add_col_groups

Examples

mat <- matrix(rnorm(24), ncol = 6)
annotation <- data.frame(gender = c(rep("M", 3),rep("F",3)),
                        age = c(20,34,27,19,23,30))
hm <- iheatmap(mat) %>% add_col_annotation(annotation)

# Print heatmap if interactive session 
if (interactive()) hm

add_col_barplot

Description

Add bar plot with one bar per column above or below a main heatmap

Usage

## S4 method for signature 'Iheatmap'
add_col_barplot(
  p,
  y,
  ...,
  color = NULL,
  tracename = NA_character_,
  showlegend = !is.na(tracename),
  side = c("top", "bottom"),
  layout = list(),
  size = 0.2,
  buffer = 0.02,
  xname = current_xaxis(p),
  yname = NULL,
  pname = if (!is.na(tracename)) tracename else "col_barplot"
)

Arguments

p

iheatmap object
y

y axis values
...

additional arguments to add to plotly scatter trace, see https://plotly.com/javascript/reference/#scatter
color

color of bars
tracename

name of trace (for legend and hover)
showlegend

show in legend?
side

side of plot on which to add subplot
layout

yaxis layout list
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
pname

internal name of plot

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_col_signal, iheatmap, add_col_plot

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- iheatmap(mat) %>% add_col_barplot(y = 1:5, tracename = "Strength")

# Print heatmap if interactive session 
if (interactive()) hm

add_col_clustering

Description

add_col_clustering

Usage

## S4 method for signature 'Iheatmap'
add_col_clustering(
  p,
  method = c("hclust", "kmeans", "groups"),
  name = "Col<br>Clusters",
  k = NULL,
  groups = NULL,
  clust_dist = stats::dist,
  colors = NULL,
  show_colorbar = TRUE,
  side = c("top", "bottom"),
  yname = NULL,
  xname = current_xaxis(p)
)

Arguments

p

iheatmap object
method

"hclust" or "kmeans" for hierarchical or k-means clustering, respectively
name

name of colorbar indicating cluster membership
k

number of clusters for rows, needed if order is kmeans or optional if hclust
groups

vector of group assignments
clust_dist

distance function to use for clustering if hierarchical clustering
colors

colors to use for annotation of grouping, can be RColorBrewer palette name or vector of colors
show_colorbar

show the colorbar for the heatmap indicating cluster membership
side

side of plot on which to add subplot
yname

name of yaxis
xname

name of xaxis

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_clustering, iheatmap

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)
hm <- iheatmap(mat) %>% add_col_clustering(method = "hclust", k = 2)

# Print heatmap if interactive session 
if (interactive()) hm

add_col_clusters

Description

Add column groups and order columns based on groups

Usage

## S4 method for signature 'Iheatmap'
add_col_clusters(
  p,
  clusters,
  name = "Col<br>Clusters",
  reorder = TRUE,
  side = c("top", "bottom"),
  xname = current_xaxis(p),
  ...
)

Arguments

p

iheatmap object
clusters

cluster assignments, should be vector of integers, characters, or factors
name

name of colorbar indicating cluster membership
reorder

reorder rows based on clusters? default is TRUE
side

side of plot on which to add subplot
xname

name of xaxis
...

additional arguments to pass to add_col_groups for creation of annotation heatmap indicating cluster membership

Details

This function is very similar to add_col_groups; the main difference is that with this function column will get reordered based on the groups.

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_clusters, add_col_clustering, iheatmap

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)
clusters <- c("A","B","A","B","A")

hm <- iheatmap(mat) %>% add_col_clusters(clusters)

# Print heatmap if interactive session 
if (interactive()) hm

add_col_dendro

Description

Adds column dendrogram to iheatmap object

Usage

## S4 method for signature 'Iheatmap,hclust'
add_col_dendro(
  p,
  dendro,
  reorder = TRUE,
  side = c("top", "bottom"),
  size = 0.15,
  buffer = 0.005,
  xname = current_xaxis(p),
  yname = NULL,
  sname = "col_dendro"
)

Arguments

p

iheatmap object
dendro

hclust object
reorder

reorder rows based on dendrogram order?
side

side of plot on which to add dendro
size

relative size of dendrogram (relative to the main heatmap)
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
sname

internal name of shape

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_col_clustering, iheatmap, add_row_dendro

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
dend <- hclust(dist(t(mat)))
hm <- iheatmap(mat) %>% add_col_dendro(dend)

# Print heatmap if interactive session 
if (interactive()) hm

add_col_groups

Description

Adds annotation to heatmap indicating what group every column of main heatmap belongs to

Usage

## S4 method for signature 'Iheatmap'
add_col_groups(
  p,
  groups,
  name = "Column<br>Groups",
  title = "Groups",
  colors = pick_discrete_colors(groups, p),
  colorbar_position = get_colorbar_position(p),
  show_colorbar = TRUE,
  show_title = TRUE,
  side = c("top", "bottom"),
  layout = list(),
  size = 0.05,
  buffer = 0.015,
  tooltip = setup_tooltip_options(),
  xname = current_xaxis(p),
  yname = NULL,
  pname = name
)

Arguments

p

Iheatmap-class object
groups

vector of group names
name

name of colorbar
title

name of x axis label
colors

palette name or vector of colors
colorbar_position

colorbar placement
show_colorbar

show the colorbar?
show_title

show title as axis label
side

side of plot on which to groups annotation
layout

list of layout parameters for x axis
size

relative size of dendrogram (relative to the main heatmap)
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
tooltip

tooltip options, see setup_tooltip_options
xname

internal name of xaxis
yname

internal name of yaxis
pname

internal name of plot

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, add_row_groups

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)
col_groups <- c("A","A","B","D","B")
hm <- iheatmap(mat) %>% add_col_groups(col_groups, name = "My Groups")

# Print heatmap if interactive session 
if (interactive()) hm

add_col_labels

Description

Add x axis labels to plot

Usage

## S4 method for signature 'Iheatmap'
add_col_labels(
  p,
  tickvals = NULL,
  ticktext = NULL,
  textangle = -90,
  font = get_layout(p)$font,
  side = c("bottom", "top"),
  size = 0.1,
  buffer = 0.005,
  xname = current_xaxis(p),
  yname = NULL
)

Arguments

p

link{Iheatmap-class} object
tickvals

column indices at which to place axis tick labels
ticktext

text for axis tick labels
textangle

angle for ticktext
font

list of plotly font attributes, see https://plotly.com/javascript/reference/#layout-font
side

side of plot on which to add subplot
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

name for xaxis
yname

name for yaxis

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_title, iheatmap, add_col_labels

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm1 <- iheatmap(mat) %>% add_col_labels()
hm2 <- iheatmap(mat) %>% add_col_labels(ticktext = letters[22:26])

# Print heatmap if interactive session 
if (interactive()) hm1
if (interactive()) hm2

add_col_plot

Description

Add a scatter or line plot with one point per column of the main heatmap

Usage

## S4 method for signature 'Iheatmap'
add_col_plot(
  p,
  y,
  ...,
  mode = c("lines+markers", "lines", "markers"),
  color = NULL,
  tracename = NA_character_,
  showlegend = !is.na(tracename),
  side = c("top", "bottom"),
  layout = list(),
  size = 0.2,
  buffer = 0.02,
  xname = current_xaxis(p),
  yname = NULL,
  pname = if (!is.na(tracename)) tracename else "col_plot"
)

Arguments

p

iheatmap object
y

y axis values
...

additional arguments to add to plotly scatter trace, see https://plotly.com/javascript/reference/#scatter
mode

mode of plot – one of "lines+markers","lines", or "markers"
color

color of bars
tracename

name of trace (for legend and hover)
showlegend

show in legend?
side

side of plot on which to add subplot
layout

yaxis layout list
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
pname

internal name of plot

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_col_signal, iheatmap, add_col_barplot

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- iheatmap(mat) %>% add_col_plot(y = 1:5, tracename = "Strength")

# Print heatmap if interactive session 
if (interactive()) hm

add_col_signal

Description

Adds column signal to iheatmap object

Usage

## S4 method for signature 'Iheatmap'
add_col_signal(
  p,
  signal,
  name,
  title = name,
  yname = NULL,
  xname = current_xaxis(p),
  pname = name,
  colorbar_position = get_colorbar_position(p),
  colors = pick_continuous_colors(zmid, zmin, zmax, p = p),
  zmin = min(signal, na.rm = TRUE),
  zmax = max(signal, na.rm = TRUE),
  zmid = 0,
  side = c("top", "bottom"),
  size = 0.05,
  buffer = 0.015,
  text = signif(signal, digits = 3),
  tooltip = setup_tooltip_options(),
  show_colorbar = TRUE,
  show_title = TRUE,
  layout = list()
)

Arguments

p

iheatmap object
signal

vector of signal
name

name of colorbar
title

label for y axis
yname

internal name of yaxis
xname

internal name of xaxis
pname

internal name of plot
colorbar_position

colorbar placement
colors

palette or vector of colors to use
zmin

minimum for colorscale
zmax

maximum for colorscale
zmid

midpoint for colorscale
side

side of plot on which to add groups
size

relative size of dendrogram (relative to the main heatmap)
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
text

text of value to display for data
tooltip

tooltip options, see setup_tooltip_options
show_colorbar

show the colorbar?
show_title

show title as axis label
layout

y axis layout parameters to use

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, add_row_groups

add_row_signal, iheatmap, add_col_annotation

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- iheatmap(mat) %>% add_col_signal(signal = 1:5, name = "Strength")

# Print heatmap if interactive session 
if (interactive()) hm

add_col_summary

Description

Adds a line plot summarizing the values across columns

Usage

## S4 method for signature 'Iheatmap'
add_col_summary(
  p,
  groups = NULL,
  heatmap_name = NULL,
  colors = NULL,
  tracename = "Col Summary",
  showlegend = FALSE,
  side = c("top", "bottom"),
  layout = list(),
  size = 0.3,
  buffer = 0.02,
  xname = current_xaxis(p),
  yname = NULL,
  type = c("scatter", "bar"),
  summary_function = c("mean", "median", "sd", "var", "mad", "max", "min", "sum"),
  ...
)

Arguments

p

Iheatmap-class object
groups

vector of group labels, name of groups colorbar, or TRUE – see Details
heatmap_name

name of a heatmap within the plot
colors

vector of colors or RColorBrewer palette name
tracename

name of trace
showlegend

show legend?
side

side of plot on which to add subplot
layout

xaxis layout list
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
type

scatter or bar?
summary_function

summary function to use, default is mean, options are mean, median, sd, var, mad, max, min, and sum
...

additional arguments to add_col_plot or add_col_barplot

Details

If adding the column summary to a vertically oriented heatmap, the summary will be based on the topmost heatmap if side is "top" and based on the bottom heatmap if side is "bottom" unless a "heatmap_name" is specified. The heatmap_name should match the "pname" argument given to a previously added heatmap.

The column summary is based on specific rows if a "groups" argument is given. The groups argument can either be a vector of group assignments for each row, the "pname" for an existing set of groups incorporated into the plot using add_row_groups, add_row_annotation, add_row_clusters, or add_row_clustering. If groups is set to TRUE, then the function will use an existing set of row groups added to the plot.

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_summary, iheatmap, add_col_plot

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm1 <- iheatmap(mat) %>% add_col_summary()
hm2 <- iheatmap(mat) %>% add_col_summary(groups = c("A","A","B","B"))

# Print heatmap if interactive session 
if (interactive()) hm1
if (interactive()) hm2

add_col_title

Description

Add x axis title to plot

Usage

## S4 method for signature 'Iheatmap'
add_col_title(
  p,
  title,
  textangle = 0,
  font = get_layout(p)$font,
  side = c("bottom", "top"),
  size = 0.1,
  buffer = 0.01,
  xname = current_xaxis(p),
  yname = NULL
)

Arguments

p

iheatmap object
title

title of axis
textangle

angle of text
font

list of plotly font attributes, see https://plotly.com/javascript/reference/#layout-font
side

side of plot on which to add subplot
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

name for xaxis
yname

name for yaxis

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_col_labels, iheatmap, add_row_title

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- iheatmap(mat) %>% add_col_title("My x-axis")

# Print heatmap if interactive session 
if (interactive()) hm

add_iheatmap

Description

add_iheatmap

Usage

## S4 method for signature 'IheatmapHorizontal,matrix'
add_iheatmap(
  p,
  data,
  x = default_x(data),
  cluster_cols = c("none", "hclust", "kmeans", "groups"),
  col_clusters = NULL,
  col_k = NULL,
  col_clust_dist = stats::dist,
  name = "Signal",
  scale = c("none", "rows", "cols"),
  scale_method = c("standardize", "center", "normalize"),
  colors = NULL,
  col_clusters_colors = NULL,
  col_clusters_name = "Col<br>Clusters",
  show_col_clusters_colorbar = TRUE,
  row_annotation = NULL,
  col_annotation = NULL,
  row_annotation_colors = NULL,
  col_annotation_colors = NULL,
  row_labels = NULL,
  col_labels = NULL,
  row_title = NULL,
  col_title = NULL,
  buffer = 0.2,
  ...
)

## S4 method for signature 'IheatmapVertical,matrix'
add_iheatmap(
  p,
  data,
  y = default_y(data),
  cluster_rows = c("none", "hclust", "kmeans", "groups"),
  row_clusters = NULL,
  row_k = NULL,
  row_clust_dist = stats::dist,
  name = "Signal",
  scale = c("none", "rows", "cols"),
  scale_method = c("standardize", "center", "normalize"),
  colors = NULL,
  row_clusters_colors = NULL,
  row_clusters_name = "Col<br>Clusters",
  show_row_clusters_colorbar = TRUE,
  row_annotation = NULL,
  col_annotation = NULL,
  row_annotation_colors = NULL,
  col_annotation_colors = NULL,
  row_labels = NULL,
  col_labels = NULL,
  row_title = NULL,
  col_title = NULL,
  buffer = 0.2,
  ...
)

Arguments

p

iheatmap object
data

matrix of values to be plotted as heatmap
x

x xaxis labels, by default colnames of data
cluster_cols

"none","hclust", or "k-means" for no clustering, hierarchical clustering, and k-means clustering of columnsrespectively
col_clusters

vector of pre-determined column cluster assignment
col_k

number of clusters for columns, needed if cluster_rows is kmeans or optional if hclust
col_clust_dist

distance function to use for column clustering if hierarchical clustering
name

Name for colorbar
scale

scale matrix by rows, cols or none
scale_method

what method to use for scaling, either standardize, center, normalize
colors

name of RColorBrewer palette or vector of colors for main heatmap
col_clusters_colors

colors for col clusters annotation heatmap
col_clusters_name

name for col clusters colorbar
show_col_clusters_colorbar

show the colorbar for column clusters?
row_annotation

row annotation data.frame
col_annotation

column annotation data.frame
row_annotation_colors

list of colors for row annotations heatmap
col_annotation_colors

list of colors for col annotations heatmap
row_labels

axis labels for y axis
col_labels

axis labels for x axis
row_title

x axis title
col_title

y axis title
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
...

additional argument to add_iheatmap
y

y axis labels, by default rownames of data
cluster_rows

"none","hclust", or "k-means" for no clustering, hierarchical clustering, and k-means clustering of rows respectively
row_clusters

vector of pre-determined row cluster assignment
row_k

number of clusters for rows, needed if cluster_rows is kmeans or optional if hclust
row_clust_dist

distance function to use for row clustering if hierarchical clustering
row_clusters_colors

colors for row clusters annotation heatmap
row_clusters_name

name for row clusters colorbar
show_row_clusters_colorbar

show the colorbar for row clusters?

Details

By default, no scaling is done of rows or columns. This can be changed by specifying the 'scale' argument. There are three options for scaling methods. "standardize" subtracts the mean and divides by standard deviation, "center" just subtracts the mean, and "normalize" divides by the sum of the values. "normalize" should only be used for data that is all positive! If alternative scaling is desired, the scaling should be done prior to calling the iheatmap function.

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, main_heatmap

Examples

mat <- matrix(rnorm(24), nrow = 6)
mat2 <- matrix(rnorm(24), nrow = 6)
annotation = data.frame(gender = c(rep("M", 3),rep("F",3)),
                        age = c(20,34,27,19,23,30))
hm <- iheatmap(mat, 
 cluster_rows = "hclust", 
 cluster_cols = "hclust", 
 col_k = 3) %>%
add_iheatmap(mat2, 
 cluster_cols = "hclust", 
 col_k = 3, 
 row_annotation = annotation)

# Print heatmap if interactive session 
if (interactive()) hm

add_main_heatmap

Description

Adds an additional main heatmap to an iheatmap object

Usage

## S4 method for signature 'IheatmapHorizontal,matrix'
add_main_heatmap(
  p,
  data,
  name = "Signal",
  x = default_x(data),
  colors = pick_continuous_colors(zmid, zmin, zmax, p),
  colorbar_position = get_colorbar_position(p),
  show_colorbar = TRUE,
  zmin = min(data, na.rm = TRUE),
  zmax = max(data, na.rm = TRUE),
  zmid = 0,
  col_order = NULL,
  x_categorical = NULL,
  side = c("right", "left"),
  size = 1,
  buffer = 0.04,
  text = signif(data, digits = 3),
  tooltip = setup_tooltip_options(),
  xname = NULL,
  pname = name,
  ...
)

## S4 method for signature 'IheatmapVertical,matrix'
add_main_heatmap(
  p,
  data,
  name = "Signal",
  y = default_y(data),
  colors = pick_continuous_colors(zmid, zmin, zmax, p),
  colorbar_position = get_colorbar_position(p),
  show_colorbar = TRUE,
  zmin = min(data, na.rm = TRUE),
  zmax = max(data, na.rm = TRUE),
  zmid = 0,
  row_order = NULL,
  y_categorical = NULL,
  side = c("bottom", "top"),
  size = 1,
  buffer = 0.04,
  text = signif(data, digits = 3),
  tooltip = setup_tooltip_options(),
  yname = NULL,
  pname = name,
  ...
)

Arguments

p

Iheatmap-class object
data

matrix
name

name of colorbar, will determine if colorbar is shared with existing plot
x

x axis labels (by default rownames of data); only used if orientation is horizontal
colors

color palette name or vector of colors
colorbar_position

colorbar placement
show_colorbar

display the colorbar?
zmin

minimum for colorscale
zmax

maximum for colorscale
zmid

midpoint for scale
col_order

column ordering for this heatmap; only used if orientation is horizontal
x_categorical

is x categorical? will guess if not provided
side

which side of the current plot to add this heatmap?
size

relative size of plot. size relative to first heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
text

text of value to display for data
tooltip

tooltip options, see setup_tooltip_options
xname

internal name for x axis
pname

internal name for plot
...

additional arguments (ignored)
y

y axis labels (by default colnames of data); only used if orientation is vertical
row_order

row ordering for this heatmap; only used if orientation is vertical
y_categorical

is y categorical? will guess if not provided
yname

internal name for y axis

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, main_heatmap

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4) 
mat2 <-  matrix(rnorm(24), ncol = 6, nrow = 4) 
hm <- iheatmap(mat) %>% add_main_heatmap(mat2)

# Print heatmap if interactive session 
if (interactive()) hm

add_row_annotation

Description

Adds annotation heatmaps for one or more qualitative or quantitative annotations for each row of a main heatmap.

Usage

## S4 method for signature 'Iheatmap'
add_row_annotation(
  p,
  annotation,
  colors = NULL,
  side = c("right", "left"),
  size = 0.05,
  buffer = 0.015,
  inner_buffer = buffer/2,
  layout = list(),
  show_colorbar = TRUE
)

Arguments

p

link{Iheatmap-class} object
annotation

data.frame or object that can be converted to data frame
colors

list of color palettes, with one color per annotation column name
side

side of plot on which to add row annotation
size

relative size of each row annotation
buffer

relative size of buffer between previous subplot and row annotation
inner_buffer

relative size of buffer between each annotation
layout

layout properties for new x axis
show_colorbar

logical indicator to show or hide colorbar

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, add_row_annotation, add_col_signal, add_col_groups

Examples

mat <- matrix(rnorm(24), nrow = 6)
annotation <- data.frame(gender = c(rep("M", 3),rep("F",3)),
                        age = c(20,34,27,19,23,30))
hm <- iheatmap(mat) %>% add_row_annotation(annotation)

# Print heatmap if interactive session 
if (interactive()) hm

add_row_barplot

Description

add_row_barplot

Usage

## S4 method for signature 'Iheatmap'
add_row_barplot(
  p,
  x,
  ...,
  color = NULL,
  tracename = NA_character_,
  showlegend = !is.na(tracename),
  side = c("right", "left"),
  layout = list(),
  size = 0.2,
  buffer = 0.02,
  xname = NULL,
  yname = current_yaxis(p),
  pname = if (!is.na(tracename)) tracename else "row_barplot"
)

Arguments

p

iheatmap object
x

x axis values
...

additional arguments to add to plotly scatter trace, see https://plotly.com/javascript/reference/#scatter
color

color of bars
tracename

name of trace (for legend and hover)
showlegend

show in legend?
side

side of plot on which to add subplot
layout

yaxis layout list
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
pname

internal name of plot

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_signal, iheatmap, add_row_plot

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- iheatmap(mat) %>% add_row_barplot(x = 1:4, tracename = "Strength")

# Print heatmap if interactive session 
if (interactive()) hm

add_row_clustering

Description

add_row_clustering

Usage

## S4 method for signature 'Iheatmap'
add_row_clustering(
  p,
  method = c("hclust", "kmeans", "groups"),
  name = "Row<br>Clusters",
  k = NULL,
  groups = NULL,
  clust_dist = stats::dist,
  colors = NULL,
  show_colorbar = TRUE,
  side = c("left", "right"),
  xname = NULL,
  yname = current_yaxis(p)
)

Arguments

p

iheatmap object
method

"hclust" or "kmeans" for hierarchical or k-means clustering, respectively
name

name of colorbar indicating cluster membership
k

number of clusters for rows, needed if order is kmeans or optional if hclust
groups

vector of group assignments
clust_dist

distance function to use for clustering if hierarchical clustering
colors

colors to use for annotation of grouping, can be RColorBrewer palette name or vector of colors
show_colorbar

show the colorbar for the heatmap indicating cluster membership
side

side of plot on which to add subplot
xname

name of xaxis
yname

name of yaxis

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_col_clustering, iheatmap

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)
hm <- iheatmap(mat) %>% add_row_clustering(method = "hclust", k = 2)

# Print heatmap if interactive session 
if (interactive()) hm

add_row_clusters

Description

Add row groups and order rows based on groups

Usage

## S4 method for signature 'Iheatmap'
add_row_clusters(
  p,
  clusters,
  name = "Row<br>Clusters",
  reorder = TRUE,
  side = c("left", "right"),
  yname = current_yaxis(p),
  ...
)

Arguments

p

iheatmap object
clusters

cluster assignments, should be vector of integers, characters, or factors
name

name of colorbar indicating cluster membership
reorder

reorder rows based on clusters? default is TRUE
side

side of plot on which to add subplot
yname

name of yaxis
...

additional arguments to pass to add_row_groups for creation of annotation heatmap indicating cluster membership

Details

This function is very similar to add_row_groups; the main difference is that with this function rows will get reordered based on the groups.

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_clustering, add_col_clusters, iheatmap

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)
clusters <- c("A","B","A","B")

hm <- iheatmap(mat) %>% add_row_clusters(clusters)

# Print heatmap if interactive session 
if (interactive()) hm

add_row_dendro

Description

Adds row dendrogram to iheatmap object

Usage

## S4 method for signature 'Iheatmap,hclust'
add_row_dendro(
  p,
  dendro,
  reorder = TRUE,
  side = c("left", "right"),
  size = 0.15,
  buffer = 0.005,
  xname = NULL,
  yname = current_yaxis(p),
  sname = "row_dendro"
)

Arguments

p

iheatmap object
dendro

hclust object
reorder

reorder rows based on dendrogram order?
side

side of plot on which to add dendrogram
size

relative size of dendrogram (relative to the main heatmap)
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
sname

internal name of shapes

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_clustering, iheatmap, add_col_dendro

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
dend <- hclust(dist(mat))
hm <- iheatmap(mat) %>% add_row_dendro(dend)

# Print heatmap if interactive session 
if (interactive()) hm

add_row_groups

Description

Adds annotation to heatmap indicating what group every row of main heatmap belongs to

Usage

## S4 method for signature 'Iheatmap'
add_row_groups(
  p,
  groups,
  name = "Row<br>Groups",
  title = "Groups",
  colors = pick_discrete_colors(groups, p),
  colorbar_position = get_colorbar_position(p),
  show_colorbar = TRUE,
  show_title = TRUE,
  side = c("right", "left"),
  layout = list(),
  size = 0.05,
  buffer = 0.005,
  tooltip = setup_tooltip_options(),
  xname = NULL,
  yname = current_yaxis(p),
  pname = name
)

Arguments

p

Iheatmap-class object
groups

vector of group names
name

name of colorbar
title

name of x axis label
colors

palette name or vector of colors
colorbar_position

colorbar placement
show_colorbar

show the colorbar?
show_title

show title as axis label
side

side of plot on which to groups annotation
layout

list of layout parameters for x axis
size

relative size of dendrogram (relative to the main heatmap)
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
tooltip

tooltip options, see setup_tooltip_options
xname

internal name of xaxis
yname

internal name of yaxis
pname

internal name of plot

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, add_col_groups

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)
row_groups <- c("A","A","B","D")
hm <- iheatmap(mat) %>% add_row_groups(row_groups, name = "My Groups")

# Print heatmap if interactive session 
if (interactive()) hm

add_row_labels

Description

Add y axis labels to plot

Usage

## S4 method for signature 'Iheatmap'
add_row_labels(
  p,
  tickvals = NULL,
  ticktext = NULL,
  textangle = 0,
  font = get_layout(p)$font,
  side = c("left", "right"),
  size = 0.1,
  buffer = 0.005,
  xname = NULL,
  yname = current_yaxis(p)
)

Arguments

p

Iheatmap-class object
tickvals

row indices at which to place axis tick labels
ticktext

text for axis tick labels
textangle

angle for ticktext
font

list of plotly font attributes, see https://plotly.com/javascript/reference/#layout-font
side

side of plot on which to add subplot
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name for xaxis
yname

internal name for yaxis

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_title, iheatmap, add_col_labels

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm1 <- iheatmap(mat) %>% add_row_labels()
hm2 <- iheatmap(mat) %>% add_row_labels(ticktext = letters[23:26])


# Print heatmaps if interactive session 
if (interactive()) hm1
if (interactive()) hm2

add_row_plot

Description

Add a scatter or line plot with one point per row of the main heatmap

Usage

## S4 method for signature 'Iheatmap'
add_row_plot(
  p,
  x,
  ...,
  mode = c("lines+markers", "lines", "markers"),
  color = NULL,
  tracename = NA_character_,
  showlegend = !is.na(tracename),
  side = c("right", "left"),
  layout = list(),
  size = 0.2,
  buffer = 0.02,
  xname = NULL,
  yname = current_yaxis(p),
  pname = if (!is.na(tracename)) tracename else "row_plot"
)

Arguments

p

iheatmap object
x

x axis values
...

additional arguments to add to plotly scatter trace, see https://plotly.com/javascript/reference/#scatter
mode

mode of plot – one of "lines+markers","lines", or "markers"
color

color of bars
tracename

name of trace (for legend and hover)
showlegend

show in legend?
side

side of plot on which to add subplot
layout

yaxis layout list
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
pname

internal name of plot

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_signal, iheatmap, add_row_barplot

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- iheatmap(mat) %>% add_row_plot(x = 1:4, tracename = "Strength")

# Print heatmap if interactive session 
if (interactive()) hm

add_row_signal

Description

Adds single column heatmap to iheatmap object

Usage

## S4 method for signature 'Iheatmap'
add_row_signal(
  p,
  signal,
  name,
  title = name,
  xname = NULL,
  yname = current_yaxis(p),
  pname = name,
  colorbar_position = get_colorbar_position(p),
  colors = pick_continuous_colors(zmid, zmin, zmax, p = p),
  zmin = min(signal, na.rm = TRUE),
  zmax = max(signal, na.rm = TRUE),
  zmid = 0,
  side = c("right", "left"),
  size = 0.05,
  buffer = 0.015,
  text = signif(signal, digits = 3),
  tooltip = setup_tooltip_options(),
  show_colorbar = TRUE,
  show_title = TRUE,
  layout = list()
)

Arguments

p

iheatmap object
signal

vector of signal
name

name of colorbar
title

label for x axis
xname

internal name of xaxis
yname

internal name of yaxis
pname

internal name of plot
colorbar_position

colorbar placement
colors

color palette or vector of colors
zmin

minimum for colorscale
zmax

maximum for colorscale
zmid

midpoint for colorscale
side

side of plot on which to add dendro
size

relative size of dendrogram (relative to the main heatmap)
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
text

text of value to display for data
tooltip

tooltip options, see setup_tooltip_options
show_colorbar

show the colorbar?
show_title

show title as axis label
layout

list of x axis layout parameters

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, add_col_groups

add_col_signal, iheatmap, add_row_annotation

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- iheatmap(mat) %>% add_row_signal(signal = 1:4, name = "Strength")

# Print heatmap if interactive session 
if (interactive()) hm

add_row_summary

Description

Adds a line plot summarizing the values across rows

Usage

## S4 method for signature 'Iheatmap'
add_row_summary(
  p,
  groups = NULL,
  heatmap_name = NULL,
  colors = NULL,
  tracename = "Row Summary",
  showlegend = FALSE,
  side = c("right", "left"),
  layout = list(),
  size = 0.3,
  buffer = 0.02,
  xname = NULL,
  yname = current_yaxis(p),
  type = c("scatter", "bar"),
  summary_function = c("mean", "median", "sd", "var", "mad", "max", "min", "sum"),
  ...
)

Arguments

p

Iheatmap-class object
groups

vector of group labels, name of groups colorbar, or TRUE – see Details
heatmap_name

name of a heatmap within the Iheatmap-class object
colors

vector of colors or RColorBrewer palette name
tracename

name of trace
showlegend

show legend?
side

side of plot on which to add subplot
layout

xaxis layout list
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
type

scatter or bar?
summary_function

summary function to use, default is mean, options are mean, median, sd, var, mad, max, min, and sum
...

additional arguments to add_row_plot or add_row_barplot

Details

If adding the row summary to a horizontally oriented heatmap, the summary will be based on the right-most heatmap if side is "right" and based on the left heatmap if side is "left" unless a "heatmap_name" is specified. The heatmap_name should match the "pname" argument given to a previously added heatmap.

The row summary is based on specific columns if a "groups" argument is given. The groups argument can either be a vector of group assignments for each row, the "pname" for an existing set of groups incorporated into the plot using add_col_groups, add_col_annotation, add_col_clusters, or add_col_clustering. If groups is set to TRUE, then the function will use an existing set of column groups added to the plot.

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_col_summary, iheatmap, add_row_plot

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm1 <- iheatmap(mat) %>% add_row_summary()
hm2 <- iheatmap(mat) %>% add_row_summary(groups = c("A","A","B","B","B"))

# Print heatmap if interactive session 
if (interactive()) hm1
if (interactive()) hm2

add_row_title

Description

Add y axis title to plot

Usage

## S4 method for signature 'Iheatmap'
add_row_title(
  p,
  title,
  textangle = ifelse(side == "left", -90, 90),
  font = get_layout(p)$font,
  side = c("left", "right"),
  size = 0.1,
  buffer = 0.01,
  xname = NULL,
  yname = current_yaxis(p)
)

Arguments

p

iheatmap object
title

title of axis
textangle

angle of text
font

list of plotly font attributes, see https://plotly.com/javascript/reference/#layout-font
side

side of plot on which to add subplot
size

relative size of subplot relative to main heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name for xaxis
yname

internal name for yaxis

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_col_title, iheatmap, add_row_labels

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- iheatmap(mat) %>% add_row_title("Samples")

# Print heatmap if interactive session 
if (interactive()) hm

add_subplot

Description

Adds an arbitrary subplot to iheatmap

Usage

## S4 method for signature 'Iheatmap'
add_subplot(
  p,
  ...,
  side = c("top", "bottom", "right", "left"),
  layout = list(),
  size = 1,
  buffer = 0.1,
  xname = if (side %in% c("top", "bottom")) current_xaxis(p) else NULL,
  yname = if (side %in% c("left", "right")) current_yaxis(p) else NULL,
  pname = "subplot"
)

Arguments

p

iheatmap object
...

arguments to pass to plotly trace, see plotly.js documentation at https://plotly.com/javascript/reference/
side

which side of the current plot to add this heatmap? "right", "left","top", or "bottom"
layout

axis layout parameters (list)
size

relative size of plot. size relative to first heatmap
buffer

amount of space to leave empty before this plot, relative to size of first heatmap
xname

internal name of xaxis
yname

internal name of yaxis
pname

internal name of plot

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap

Examples

mat <- matrix(rnorm(24), ncol = 6)
hm <- iheatmap(mat) %>% add_subplot(x = 1:5, y=1:5, side = "top")

# Print heatmap if interactive session 
if (interactive()) hm

iheatmap

Description

Make a farily standard interactive heatmap with optional clustering and row and column annotations. For more flexibility and options, see the main_heatmap function and other modular functions as described in vignette.

Usage

## S4 method for signature 'matrix'
iheatmap(
  data,
  x = default_x(data),
  y = default_y(data),
  cluster_rows = c("none", "hclust", "kmeans"),
  cluster_cols = c("none", "hclust", "kmeans"),
  row_clusters = NULL,
  col_clusters = NULL,
  row_k = NULL,
  col_k = NULL,
  row_clust_dist = stats::dist,
  col_clust_dist = stats::dist,
  name = "Signal",
  scale = c("none", "rows", "cols"),
  scale_method = c("standardize", "center", "normalize"),
  colors = NULL,
  col_clusters_colors = NULL,
  col_clusters_name = "Col<br>Clusters",
  row_clusters_colors = NULL,
  row_clusters_name = "Row<br>Clusters",
  show_row_clusters_colorbar = TRUE,
  show_col_clusters_colorbar = TRUE,
  row_annotation = NULL,
  col_annotation = NULL,
  row_annotation_colors = NULL,
  col_annotation_colors = NULL,
  row_labels = NULL,
  col_labels = NULL,
  row_title = NULL,
  col_title = NULL,
  colorbar_grid = setup_colorbar_grid(),
  layout = list(),
  source = "iheatmapr",
  ...
)

Arguments

data

matrix of values to be plotted as heatmap
x

x xaxis labels, by default colnames of data
y

y axis labels, by default rownames of data
cluster_rows

"none","hclust", or "k-means" for no clustering, hierarchical clustering, and k-means clustering of rows respectively
cluster_cols

"none","hclust", or "k-means" for no clustering, hierarchical clustering, and k-means clustering of columnsrespectively
row_clusters

vector of pre-determined row cluster assignment
col_clusters

vector of pre-determined column cluster assignment
row_k

number of clusters for rows, needed if cluster_rows is kmeans or optional if hclust
col_k

number of clusters for columns, needed if cluster_rows is kmeans or optional if hclust
row_clust_dist

distance function to use for row clustering if hierarchical clustering
col_clust_dist

distance function to use for column clustering if hierarchical clustering
name

Name for colorbar
scale

scale matrix by rows, cols or none
scale_method

what method to use for scaling, either none, standardize, center, normalize
colors

name of RColorBrewer palette or vector of colors for main heatmap
col_clusters_colors

colors for col clusters annotation heatmap
col_clusters_name

name for col clusters colorbar
row_clusters_colors

colors for row clusters annotation heatmap
row_clusters_name

name for row clusters colorbar
show_row_clusters_colorbar

show the colorbar for row clusters?
show_col_clusters_colorbar

show the colorbar for column clusters?
row_annotation

row annotation data.frame
col_annotation

column annotation data.frame
row_annotation_colors

list of colors for row annotations heatmap
col_annotation_colors

list of colors for col annotations heatmap
row_labels

axis labels for y axis
col_labels

axis labels for x axis
row_title

x axis title
col_title

y axis title
colorbar_grid

colorbar grid parameters, should be result from setup_colorbar_grid
layout

list of layout attributes to pass to plotly, eg. list(font = list(size = 15))
source

source name for use with shiny
...

additional argument to iheatmap

Details

By default, no scaling is done of rows or columns. This can be changed by specifying the 'scale' argument. There are three options for scaling methods. "standardize" subtracts the mean and divides by standard deviation, "center" just subtracts the mean, and "normalize" divides by the sum of the values. "normalize" should only be used for data that is all positive! If alternative scaling is desired, the scaling should be done prior to calling the iheatmap function.

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

iheatmap, add_iheatmap, to_widget

Examples

mat <- matrix(rnorm(24), nrow = 6)
annotation = data.frame(gender = c(rep("M", 3),rep("F",3)),
 age = c(20,34,27,19,23,30))
hm <- iheatmap(mat, 
 cluster_rows = "hclust",
 cluster_cols = "kmeans", 
 col_k = 3, 
 row_annotation = annotation)

# Print heatmap if interactive session 
if (interactive()) hm

Iheatmap-class

Description

Class to store complex interactive heatmap objects from iheatmapr package

Details

This is a virtual class with two children classes, IheatmapHorizontal and IheatmapVertical. For IheatmapHorizontal additional main heatmaps are added horizontally, and for IheatmapVertical additional main heatmaps are added vertically. For details on accessing certain slots of this class, see access_component documentation.

Slots

plots

list of plot element in IheatmapPlots format

shapes

list of shape element in IheatmapShapes format

annotations

list of annotation elements in IheatmapAnnotations format

xaxes

list of x axes in IheatmapAxes format

yaxes

list of y axes in IheatmapAxes format

colorbars

list of colorbars in IheatmapColorbars format

colorbar_grid

colorbar grid parameters in IheatmapColorbarGrid format

current_xaxis

name of current x axis

current_yaxis

name of current y axis

layout

list of plotly layout parameters

source

source name, for use with shiny

Author(s)

Alicia Schep

See Also

iheatmap, main_heatmap, access_component

iheatmapr

Description

Interactive complex heatmaps in R

Details

iheatmapr is a package for building complex, interactive heatmaps in R that can be explored in interactive R sessions or incorporated into rmarkdown documents, shiny applications, or standalone html files.

The package includes a modular system for building up complex heatmaps, where subplots get iteratively added to the top/left/right/bottom of the main heatmap(s). The iheatmap function provides a wrapper around many of the common modular subcomponents to build fairly standard, moderately complex heatmap.

See the vignette for detailed instructions for how to use the package.

iheatmapr uses the plotly javascript library (https://plotly.com/) for making the interactive figures and htmlwidgets (http://www.htmlwidgets.org/) for rendering them in R.

Author(s)

Alicia Schep

See Also

main_heatmap, iheatmap, Iheatmap-class

Access iheatmapr user input event data in shiny

Description

This function must be called within a reactive shiny context.

Usage

iheatmapr_event(
  object,
  event = c("hover", "click", "relayout"),
  session = shiny::getDefaultReactiveDomain()
)

Arguments

object

Iheatmap-class object
event

The type of plotly event. Currently 'plotly_hover', 'plotly_click', 'plotly_selected', and 'plotly_relayout' are supported.
session

a shiny session object (the default should almost always be used).

Examples

## Not run: 
shiny::runApp(system.file("examples", "shiny_example", package = "iheatmapr"))

## End(Not run)

Shiny bindings for iheatmapr

Description

Output and render functions for using iheatmapr within Shiny

Usage

iheatmaprOutput(outputId, width = "100%", height = "400px")

renderIheatmap(expr, env = parent.frame(), quoted = FALSE)

Arguments

outputId

output variable to read from
width, height

Must be a valid CSS unit (like "100%", "400px", "auto") or a number, which will be coerced to a string and have "px" appended.
expr

An expression that generates an Iheatmap object
env

The environment in which to evaluate expr.
quoted

Is expr a quoted expression (with quote())? This is useful if you want to save an expression in a variable.

main_heatmap

Description

Plots initial heatmap, creates Iheatmap object

Usage

## S4 method for signature 'matrix'
main_heatmap(
  data,
  name = "Signal",
  x = default_x(data),
  y = default_y(data),
  colors = pick_continuous_colors(zmid, zmin, zmax),
  colorbar_grid = setup_colorbar_grid(),
  colorbar_position = 1,
  zmid = 0,
  zmin = min(data, na.rm = TRUE),
  zmax = max(data, na.rm = TRUE),
  orientation = c("horizontal", "vertical"),
  x_categorical = NULL,
  y_categorical = NULL,
  row_order = seq_len(nrow(data)),
  col_order = seq_len(ncol(data)),
  text = signif(data, digits = 3),
  tooltip = setup_tooltip_options(),
  xname = "x",
  yname = "y",
  pname = name,
  source = "iheatmapr",
  show_colorbar = TRUE,
  layout = list()
)

Arguments

data

matrix
name

name of colorbar
x

x axis labels (by default rownames of data)
y

y axis labels (by default colnames of data)
colors

color palette or vector of colors
colorbar_grid

colorbar grid parameters, should be result from setup_colorbar_grid
colorbar_position

colorbar placement, should be positive integer
zmid

midpoint for colorscale
zmin

minimum for colorscale
zmax

maximum for colorscale
orientation

should new main plots be added horizontally or vertically?
x_categorical

is x categorical? will guess if not provided
y_categorical

is y categorical? will guess if not provided
row_order

row ordering for this heatmap– will be used for all subsequent elements sharing y axis
col_order

column ordering for this heatmap– will be used for all subsequent elements sharing x axis
text

text of value to display for data
tooltip

tooltip options, see setup_tooltip_options
xname

internal name for xaxis
yname

internal name for yaxis
pname

internal plot name
source

source name for use with shiny
show_colorbar

logical to indicate whether to show colorbar
layout

list of layout attributes to pass to plotly, eg. list(font = list(size = 15))

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_iheatmap, to_widget, iheatmap, Iheatmap-class

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- main_heatmap(mat) 

# Print heatmap if interactive session 
if (interactive()) hm

measles

Description

Data on measles cases for different states from 1930 to 2001

Examples

data(measles)

modify_layout

Description

modify_layout

Usage

## S4 method for signature 'Iheatmap'
modify_layout(x, new_layout)

Arguments

x

Iheatmap
new_layout

list of new layout parameter

Value

modified Iheatmap object

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm <- main_heatmap(mat) %>% modify_layout(list(margin = list(b = 120))) 

# Print heatmap if interactive session 
if (interactive()) hm

reorder_cols

Description

Reorder the columns of an Iheatmap-class object

Usage

## S4 method for signature 'IheatmapHorizontal,integer'
reorder_cols(p, col_order, xname = current_xaxis(p))

## S4 method for signature 'IheatmapVertical,integer'
reorder_cols(p, col_order)

Arguments

p

Iheatmap-class object
col_order

integer vector
xname

name of xaxis to reorder, only applicable if object is oriented horizontally

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_clustering, reorder_cols

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
dend <- hclust(dist(t(mat)))
hm <- iheatmap(mat) %>% reorder_cols(dend$order)

# Print heatmap if interactive session 
if (interactive()) hm

reorder_rows

Description

Reorder the rows of an Iheatmap-class object

Usage

## S4 method for signature 'IheatmapHorizontal,integer'
reorder_rows(p, row_order)

## S4 method for signature 'IheatmapVertical,integer'
reorder_rows(p, row_order, yname = current_yaxis(p))

Arguments

p

Iheatmap-class object
row_order

integer vector
yname

name of yaxis to reorder, only applicable if object is oriented vertically

Value

Iheatmap-class object, which can be printed to generate an interactive graphic

Author(s)

Alicia Schep

See Also

add_row_clustering, reorder_cols

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
dend <- hclust(dist(mat))
hm <- iheatmap(mat) %>% reorder_rows(dend$order)

# Print heatmap if interactive session 
if (interactive()) hm

save_iheatmap

Description

save an link{Iheatmap-class} object, either as standalone HTML or as static pdf/png/jpeg

Usage

## S4 method for signature 'Iheatmap,character'
save_iheatmap(p, filename, ...)

Arguments

p

link{Iheatmap-class} object
filename

name of file
...

additional arguments to saveWidget for saving as html or webshot for saving as pdf/png/jpeg

Details

Note that this function requires the webshot package. If deploying a shiny app that calls this function in shinyapps.io, loading the webshot library and calling webshot::install_phantomjs() is needed for the the save functionality to work.

Author(s)

Alicia Schep

Examples

mat <- matrix(rnorm(24), nrow = 6)
hm <- iheatmap(mat)
## Not run: 
save_iheatmap(hm, "example_iheatmap.png")

## End(Not run)

setup_colorbar_grid

Description

function to set parameters controlling colorbar placement in Iheatmap object

Usage

setup_colorbar_grid(
  nrows = 3,
  y_length = y_spacing * 0.9,
  x_spacing = 0.16,
  y_spacing = y_start/nrows,
  x_start = 1.05,
  y_start = 0.9
)

Arguments

nrows

number of rows in colorbar grid
y_length

length of colorbar
x_spacing

spacing along horizontal axis between colorbars
y_spacing

spacing along vertical axis between colorbars
x_start

left most position of colorbar grid
y_start

top most position of colorbar grid

Value

IheatmapColorbarGrid-class object

Examples

cb_grid <- setup_colorbar_grid(nrows = 2, x_spacing = 0.2)
mat <- matrix(rnorm(24), nrow = 6)
hm <- iheatmap(mat, colorbar_grid = cb_grid, cluster_rows = "kmeans",
         cluster_cols = "kmeans", row_k = 3, col_k = 2)

# Print heatmap if interactive session 
if (interactive()) hm

Tooltip Options

Description

This function setups tooltip options for heatmap components of iheatmapr complex heatmaps.

Usage

setup_tooltip_options(
  row = TRUE,
  col = TRUE,
  value = TRUE,
  prepend_row = "Row: ",
  prepend_col = "Col: ",
  prepend_value = "Value: "
)

Arguments

row

logical, include row name in tooltip?
col

logical, include column name in tooltip?
value

logical, include value in tooltip?
prepend_row

text to prepend to row name
prepend_col

text to prepend to column name
prepend_value

text to prepend to value

Value

a HeatmapTooltipOptions object which stores these options and can be passed to 'tooltip' argument to main_heatmap and other functions.

Examples

mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
hm1 <- main_heatmap(mat, 
   tooltip = setup_tooltip_options(row = FALSE, col = FALSE,
                                   prepend_value = "Value is ")) 

# Print heatmap if interactive session 
if (interactive()) hm1

test_iheatmapr_event

Description

test_iheatmapr_event

Usage

test_iheatmapr_event(ihm, event = c("click", "hover", "relayout"))

Arguments

ihm

Iheatmap object
event

name of event, either "click","hover", or "relayout"

Value

shiny app

Examples

## Not run: 
  mat <- matrix(rnorm(20), ncol = 5, nrow = 4)  
  hm <- main_heatmap(mat) 
  test_iheatmapr_event(hm, "click")

## End(Not run)

Convert Iheatmap to plotly spec

Description

Function to convert link{Iheatmap-class} object to a plotly spec either as a list or json

Usage

to_plotly_list(p)

to_plotly_json(p)

Arguments

p

Iheatmap-class object to convert

Value

Returns a JSON for a plotly spec for to_plotly_spec and as a list of same plotly object for to_plotly_list.

Examples

mat <- matrix(rnorm(24), nrow = 6)
hm_json <- iheatmap(mat) %>% to_plotly_json()
hm_list <- iheatmap(mat) %>% to_plotly_list()

to_widget

Description

Function to convert link{Iheatmap-class} object to widget object

Usage

## S4 method for signature 'Iheatmap'
to_widget(p)

Arguments

p

Iheatmap-class object to convert

Value

htmlwidgets object

Author(s)

Alicia Schep

See Also

iheatmap, main_heatmap

Examples

mat <- matrix(rnorm(24), nrow = 6)
hm <- iheatmap(mat) %>% to_widget()
class(hm)

# Print heatmap if interactive session 
if (interactive()) hm