library(knitr) knitr::opts_chunk$set( error = FALSE, tidy = FALSE, message = FALSE, warning = FALSE, fig.width = 6, fig.height = 6, fig.align = "center" ) library(GetoptLong) options(digits = 4)
library(SC3) library(GOexpress)
With InteractiveComplexHeatmap, the following heatmaps can be exported as an interactive Shiny app:
stats::heatmap()
, gplots::heatmap.2()
and pheatmap::pheatmap()
, but can be reproduced by the "translation
functions": ComplexHeatmap:::heatmap()
, ComplexHeatmap:::heatmap.2()
and ComplexHeatmap::pheatmap()
.All these types of heatmaps can be turned into interactive just by calling
htShiny()
after the heatmaps are drawn. E.g.:
ComplexHeatmap::pheatmap(...) htShiny()
which means you don't need to touch your heatmap code. After you see the heatmap in your R terminal or generated in a file,
directly calling htShiny()
with no argument will produce an interactive heatmap, like magic. :P
Now there is a fourth scenario where the heatmap is produced by third-party
functions which internally use stats::heatmap()
, gplots::heatmap.2()
or
pheatmap::pheatmap()
. Since now we cannot directly interact with
heatmap()
, heatmap.2()
or pheatmap()
, how can we turn these heatmaps into
interactive? The solution is fairly simple. We just need to go to e.g. pheatmap
namespace and replace pheatmap
with ComplexHeatmap::pheatmap
.
The following example is from the SC3 package where
function sc3_plot_expression()
internally uses pheatmap()
.
library(SingleCellExperiment) library(SC3) library(scater) sce <- SingleCellExperiment( assays = list( counts = as.matrix(yan), logcounts = log2(as.matrix(yan) + 1) ), colData = ann ) rowData(sce)$feature_symbol <- rownames(sce) sce <- sce[!duplicated(rowData(sce)$feature_symbol), ] sce <- runPCA(sce) sce <- sc3(sce, ks = 2:4, biology = TRUE) sc3_plot_expression(sce, k = 3)
To replace the internally use of pheatmap::pheatmap
with
ComplexHeatmap::pheatmap
, we can use assignInNamespace()
to directly
change the value of pheatmap
in pheatmap namespace. After that,
recalling sc3_plot_expression()
will directly use
ComplexHeatmap::pheatmap()
and now you can use htShiny()
to export it as
an interactive app. Of course, you need to regenerate the heatmap with the
same code.
assignInNamespace("pheatmap", ComplexHeatmap::pheatmap, ns = "pheatmap") library(InteractiveComplexHeatmap) sc3_plot_expression(sce, k = 3) htShiny()
If you check the source code of sc3_plot_expression()
, pheatmap()
is used
by explicitely adding its namespace (check the last few lines of the function definition):
selectMethod("sc3_plot_expression", signature = "SingleCellExperiment")
In this case, changing pheatmap
in pheatmap namespace directly affects sc3_plot_expression()
.
However, if the heatmap function is called without adding the namespace (e.g., in previous example, the pheatmap::
prefix), you
need to first unload the package, modify the heatmap function in the heatmap
namespace and later load the package back.
Let's look at the next example from GOexpress package where the function heatmap_GO()
internally use heatmap.2()
.
library(GOexpress) data(AlvMac) set.seed(4543) AlvMac_results <- GO_analyse( eSet = AlvMac, f = "Treatment", GO_genes=AlvMac_GOgenes, all_GO=AlvMac_allGO, all_genes=AlvMac_allgenes) BP.5 <- subset_scores( result = AlvMac_results.pVal, namespace = "biological_process", total = 5, p.val=0.05) heatmap_GO( go_id = "GO:0034142", result = BP.5, eSet=AlvMac, cexRow=0.4, cexCol=1, cex.main=1, main.Lsplit=30)
Now note in heatmap_GO()
function, heatmap.2()
is used without gplots namespace (go to
the end of the function definition listed below).
heatmap_GO
In this case, since we have already loaded the GOexpress namespace, the GOexpress namespace should firstly be removed by
detach()
, or else heatmap_GO()
will still use gplots::heatmap.2()
.
detach("package:GOexpress", unload = TRUE) assignInNamespace("heatmap.2", ComplexHeatmap:::heatmap.2, ns = "gplots") library(GOexpress) library(InteractiveComplexHeatmap) heatmap_GO( go_id = "GO:0034142", result = BP.5, eSet=AlvMac, cexRow=0.4, cexCol=1, cex.main=1, main.Lsplit=30) htShiny()
In the end, to safely change all stats::heatmap()
, gplots::heatmap.2()
and
pheatmap::pheatmap()
to ComplexHeatmap:::heatmap()
,
ComplexHeatmap:::heatmap.2()
and ComplexHeatmap::pheatmap()
, you can add following lines
to the start of your R session:
library(pheatmap) library(gplots) assignInNamespace("heatmap", ComplexHeatmap:::heatmap, ns = "stats") assignInNamespace("heatmap.2", ComplexHeatmap:::heatmap.2, ns = "gplots") assignInNamespace("pheatmap", ComplexHeatmap::pheatmap, ns = "pheatmap")
You can find runnable examples in htShinyExample(8.1)
, htShinyExample(8.2)
and htShinyExample(8.3)
.
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