add_iheatmap {iheatmapr} | R Documentation |
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
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