ExperimentColorMap-class: ExperimentColorMap class

Description Usage Arguments Details Value Categorical colormaps Accessors Setters Examples

Description

ExperimentColorMap class

Usage

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ExperimentColorMap(
  assays = list(),
  colData = list(),
  rowData = list(),
  all_discrete = list(assays = NULL, colData = NULL, rowData = NULL),
  all_continuous = list(assays = NULL, colData = NULL, rowData = NULL),
  global_discrete = NULL,
  global_continuous = NULL,
  ...
)

Arguments

assays

List of colormaps for assays.

colData

List of colormaps for colData.

rowData

List of colormaps for rowData.

all_discrete

Colormaps applied to all undefined categorical assays, colData, and rowData, respectively.

all_continuous

Colormaps applied to all undefined continuous assays, colData, and rowData, respectively.

global_discrete

Colormap applied to all undefined categorical covariates.

global_continuous

Colormap applied to all undefined continuous covariates.

...

additional arguments passed on to the ExperimentColorMap constructor

Details

Colormaps must all be functions that take at least one argument: the number of (named) colours to return as a character vector. This argument may be ignored in the body of the colormap function to produce constant colormaps.

Value

An object of class ExperimentColorMap

Categorical colormaps

The default categorical colormap emulates the default ggplot2 categorical color palette (Credit: https://stackoverflow.com/questions/8197559/emulate-ggplot2-default-color-palette). This palette returns a set of colors sampled in steps of equal size that correspond to approximately equal perceptual changes in color:

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function(n) {
    hues=seq(15, 375, length=(n + 1))
    hcl(h=hues, l=65, c=100)[seq_len(n)]
}

To change the palette for all categorical variables, users must supply a colormap that returns a similar value; namely, an unnamed character vector of length n. For instance, using the base R palette rainbow.colors

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function(n) {
    rainbow(n)
}

Accessors

In the following code snippets, x is an ExperimentColorMap object. If the colormap can not immediately be found in the appropriate slot, discrete is a logical(1) that indicates whether the default colormap returned should be categorical TRUE or continuous (FALSE, default).

assayColorMap(x, i, ..., discrete=FALSE):

Get an assays colormap.

colDataColorMap(x, i, ..., discrete=FALSE):

Get a colData colormap.

rowDataColorMap(x, i, ..., discrete=FALSE):

Get a rowData colormap.

Setters

In the following code snippets, x is an ExperimentColorMap object, and i is a character or numeric index.

assayColorMap(x, i, ...) <- value:

Set an assays colormap.

colDataColorMap(x, i, ...) <- value:

Set a colData colormap.

rowDataColorMap(x, i, ...) <- value:

Set a rowData colormap.

assay(x, i, ...) <- value:

Alias. Set an assays colormap.

Examples

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# Example colormaps ----

count_colors <- function(n){
  c("black", "brown", "red", "orange", "yellow")
}
fpkm_colors <- viridis::inferno
tpm_colors <- viridis::plasma

qc_color_fun <- function(n){
  qc_colors <- c("forestgreen", "firebrick1")
  names(qc_colors) <- c("Y", "N")
  return(qc_colors)
}

# Constructor ----

ecm <- ExperimentColorMap(
    assays=list(
        counts=count_colors,
        tophat_counts=count_colors,
        cufflinks_fpkm=fpkm_colors,
        rsem_tpm=tpm_colors
    ),
    colData=list(
        passes_qc_checks_s=qc_color_fun
    )
)

# Accessors ----

# assay colormaps
assayColorMap(ecm, "logcounts") # [undefined --> default]
assayColorMap(ecm, "counts")
assayColorMap(ecm, "cufflinks_fpkm")
assay(ecm, "cufflinks_fpkm") # alias

# colData colormaps
colDataColorMap(ecm, "passes_qc_checks_s")
colDataColorMap(ecm, "undefined")

# rowData colormaps
rowDataColorMap(ecm, "undefined")

# generic accessors
assays(ecm)
assayNames(ecm)

# Setters ----

assayColorMap(ecm, "counts") <- function(n){c("blue", "white", "red")}
assay(ecm, 1) <- function(n){c("blue", "white", "red")}

colDataColorMap(ecm, "passes_qc_checks_s") <- function(n){NULL}
rowDataColorMap(ecm, "undefined") <- function(n){NULL}

# Categorical colormaps ----

# Override all discrete colormaps using the base rainbow palette
ecm <- ExperimentColorMap(global_discrete = rainbow)
n <- 10
plot(1:n, col=assayColorMap(ecm, "undefined", discrete = TRUE)(n), pch=20, cex=3)

iSEE documentation built on Feb. 3, 2021, 2:01 a.m.