Heatmap of motif enrichments.

Plot motif enrichments (e.g. significance or magnitude) as a heatmap.

plotMotifHeatmaps(
  x,
  which.plots = c("negLog10P", "pearsonResid", "negLog10Padj", "log2enr"),
  width = 4,
  col.enr = c("#053061", "#2166AC", "#4393C3", "#92C5DE", "#D1E5F0", "#F7F7F7",
    "#FDDBC7", "#F4A582", "#D6604D", "#B2182B", "#67001F"),
  col.sig = c("#F0F0F0", "#D9D9D9", "#BDBDBD", "#969696", "#737373", "#525252",
    "#252525", "#000000"),
  col.gc = c("#F7FCF5", "#E5F5E0", "#C7E9C0", "#A1D99B", "#74C476", "#41AB5D", "#238B45",
    "#006D2C", "#00441B"),
  maxEnr = NULL,
  maxSig = NULL,
  highlight = NULL,
  cluster = FALSE,
  show_dendrogram = FALSE,
  show_motif_GC = FALSE,
  show_seqlogo = FALSE,
  width.seqlogo = 1.5,
  use_raster = FALSE,
  na_col = "white",
  doPlot = TRUE,
  ...
)

Arguments

x

A SummarizedExperiment with numerical matrices (motifs-by-bins) in its assays(), typically the return value of calcBinnedMotifEnrR or calcBinnedMotifEnrHomer.

which.plots

Selects which heatmaps to plot (one or several from "negLog10P", "negLog10Padj", "pearsonResid" and "log2enr").

width

The width (in inches) of each individual heatmap, without legend.

col.enr

Colors used for enrichment heatmap ("pearsonResid" and "log2enr").

col.sig

Colors used for significance hetmaps ("negLog10P" and "negLog10Padj").

col.gc

Colors used for motif GC content (for show_motif_GC = TRUE).

maxEnr

Cap color mapping at enrichment = maxEnr (default: 99.5th percentile).

maxSig

Cap color mapping at -log10 P value or -log10 FDR = maxSig (default: 99.5th percentile).

highlight

A logical vector indicating motifs to be highlighted.

cluster

If TRUE, the order of transcription factors will be determined by hierarchical clustering of the "pearsonResid" component. Alternatively, an hclust-object can be supplied which will determine the motif ordering. No reordering is done for cluster = FALSE.

show_dendrogram

If cluster != FALSE, controls whether to show a row dendrogram for the clustering of motifs. Ignored for cluster = FALSE.

show_motif_GC

If TRUE, show a column with the percent G+C of the motif as part of the heatmap.

show_seqlogo

If TRUE, show a sequence logo next to each motif label. This will likely only make sense for a heatmap with a low number of motifs.

width.seqlogo

The width (in inches) for the longest sequence logo (shorter logos are drawn to scale).

use_raster

TRUE or FALSE (default). Passed to use_raster of Heatmap.

na_col

"white" (default). Passed to na_col of Heatmap.

doPlot

If TRUE (default), plot the generated heatmap(s) using Reduce(ComplexHeatmap::add_heatmap, heatmapList). If FALSE, just return the list of heatmap(s) (heatmapList) in example before), allowing to modify them further before plotting.

...

Further arguments passed to Heatmap when creating the main heatmaps selected by which.plots. For example, the following will set the font size of the motif names: plotMotifHeatmaps(..., row_names_gp = gpar(fontsize = 12))

Value

A list of ComplexHeatmap::Heatmap objects.

Details

The heatmaps are created using the ComplexHeatmap package and plotted side-by-side.

Each heatmap will be width inches wide, so the total plot needs a graphics device with a width of at least length(which.plots) * width plus the space used for motif names and legend. The height will be auto-adjusted to the graphics device.

References

Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 2016.

See also

bin, Heatmap

Examples

se <- readRDS(system.file("extdata", 
                          "results.binned_motif_enrichment_LMRs.rds", 
                          package = "monaLisa"))
i <- which(SummarizedExperiment::assay(se, "negLog10Padj")[, 8] > 4)
plotMotifHeatmaps(se[i, ], which.plots = "pearsonResid",
                  width = 2, show_seqlogo = TRUE)