Last updated: 2023-11-01
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Knit directory: muse/
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Rmd | 3e13eb5 | Dave Tang | 2023-11-01 | ComplexHeatmap |
Install latest version from GitHub.
remotes::install_github("jokergoo/ComplexHeatmap")
Load library.
library(ComplexHeatmap)
Download example data.
example_file <- "https://davetang.org/file/TagSeqExample.tab"
data <- read.delim(example_file, header = TRUE, row.names = "gene")
data_subset <- as.matrix(data[rowSums(data)>50000,])
dim(data_subset)
[1] 49 6
Default heatmap for ComplexHeatmap.
Heatmap(data_subset)
Normalise using z-score.
cal_z_score <- function(x){
(x - mean(x)) / sd(x)
}
data_subset_norm <- t(apply(data_subset, 1, cal_z_score))
Heatmap(data_subset_norm)
Add a title using column_title
; the name
parameter puts a title of the heatmap legend.
Heatmap(data_subset_norm, column_title = "My title", name = "Legend")
Two heatmaps.
one <- Heatmap(data_subset, column_title = "Raw", name = "Raw")
two <- Heatmap(data_subset_norm, column_title = "Scaled", name = "Scaled")
one + two
Add annotations.
set.seed(123)
mat <- matrix(rnorm(100), 10)
rownames(mat) = paste0("R", 1:10)
colnames(mat) = paste0("C", 1:10)
column_ha = HeatmapAnnotation(
foo1 = rep(c('N', 'T'), 5),
bar1 = anno_barplot(colMeans(mat))
)
row_ha = rowAnnotation(
foo2 = runif(10),
bar2 = anno_barplot(rowMeans(mat))
)
Heatmap(mat, name = "mat", top_annotation = column_ha, right_annotation = row_ha)
Heatmap(mat, name = "mat", row_km = 3, column_km = 3)
sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.3 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] grid stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] ComplexHeatmap_2.15.4 gridExtra_2.3 dendextend_1.17.1
[4] pheatmap_1.0.12 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] shape_1.4.6 circlize_0.4.15 gtable_0.3.4
[4] rjson_0.2.21 xfun_0.40 bslib_0.5.1
[7] ggplot2_3.4.4 GlobalOptions_0.1.2 processx_3.8.2
[10] callr_3.7.3 vctrs_0.6.4 tools_4.3.2
[13] ps_1.7.5 generics_0.1.3 stats4_4.3.2
[16] parallel_4.3.2 tibble_3.2.1 fansi_1.0.5
[19] cluster_2.1.4 pkgconfig_2.0.3 RColorBrewer_1.1-3
[22] S4Vectors_0.40.1 lifecycle_1.0.3 compiler_4.3.2
[25] stringr_1.5.0 git2r_0.32.0 munsell_0.5.0
[28] getPass_0.2-2 codetools_0.2-19 clue_0.3-65
[31] httpuv_1.6.12 htmltools_0.5.6.1 sass_0.4.7
[34] yaml_2.3.7 later_1.3.1 pillar_1.9.0
[37] crayon_1.5.2 jquerylib_0.1.4 whisker_0.4.1
[40] cachem_1.0.8 iterators_1.0.14 viridis_0.6.4
[43] foreach_1.5.2 tidyselect_1.2.0 digest_0.6.33
[46] stringi_1.7.12 dplyr_1.1.3 rprojroot_2.0.3
[49] fastmap_1.1.1 colorspace_2.1-0 cli_3.6.1
[52] magrittr_2.0.3 utf8_1.2.4 scales_1.2.1
[55] promises_1.2.1 rmarkdown_2.25 httr_1.4.7
[58] matrixStats_1.0.0 png_0.1-8 GetoptLong_1.0.5
[61] evaluate_0.22 knitr_1.44 IRanges_2.36.0
[64] doParallel_1.0.17 viridisLite_0.4.2 rlang_1.1.1
[67] Rcpp_1.0.11 glue_1.6.2 BiocGenerics_0.48.0
[70] rstudioapi_0.15.0 jsonlite_1.8.7 R6_2.5.1
[73] fs_1.6.3