[可视化|R包]ComplexHeatmap学习笔记③Makin
2019-07-05 本文已影响0人
郑宝童
- ComplexHeatmap学习笔记①Introduction to ComplexHeatmap package
- ComplexHeatmap学习笔记②Making A Single Heatmap
Making A List of Heatmaps 制作一组热图
A list of heatmaps可以优化多个数据源之间对应关系的可视化。在这个vignette中，我们将讨论making a list of heatmaps 的配置，您可以在[Examples]vignette 以及在ComplexHeatmap paper的[supplementaries]中看到更多真实的例子。
Heatmap concatenation 合并多个热图
你可以从左到右排列多个热图。实际上，一个单独的热图只是长度为1的heatmap list的特殊情况。
heatmap()实际上是一类单个heatmap的构造函数。如果要组合多个heatmap，用户可以通过+运算符将一个heatmap附加到另一个heatmap。
library(ComplexHeatmap)
mat1 = matrix(rnorm(80, 2), 8, 10)
mat1 = rbind(mat1, matrix(rnorm(40, -2), 4, 10))
rownames(mat1) = paste0("R", 1:12)
colnames(mat1) = paste0("C", 1:10)
mat2 = matrix(rnorm(60, 2), 6, 10)
mat2 = rbind(mat2, matrix(rnorm(60, -2), 6, 10))
rownames(mat2) = paste0("R", 1:12)
colnames(mat2) = paste0("C", 1:10)
ht1 = Heatmap(mat1, name = "ht1")
ht2 = Heatmap(mat2, name = "ht2")
class(ht1)
## [1] "Heatmap"
## attr(,"package")
## [1] "ComplexHeatmap"
class(ht2)
## [1] "Heatmap"
## attr(,"package")
## [1] "ComplexHeatmap"
ht1 + ht2
两图拼接
在默认模式下，第二个heatmap中的树形图将被删除，行顺序也将与第一个相同.
两个heatmap相加的返回值是一个heatmaplist对象。直接调用ht_list对象将调用draw()方法的默认设置。通过显式调用draw()方法，您可以拥有更多的控件，例如图例和标题。
ht_list = ht1 + ht2
class(ht_list)
## [1] "HeatmapList"
## attr(,"package")
## [1] "ComplexHeatmap"
您可以在heatmap list中附加任意数量的heatmap。还可以将heatmap list 附加到heatmap list。
ht1 + ht1 + ht1
ht1 + ht_list
ht_list + ht1
ht_list + ht_list
NULL 可以被赋值给heatmaplist中。当用户想通过for循环构造一个heatmap list时，它将是很方便的。
ht_list = NULL
for(s in sth) {
ht_list = ht_list + Heatmap(...)
}
Titles 标题
A heatmap list还具有独立于热图标题的标题。--单个heatmap有单独的标题，组合起来的heatmap list也可以弄个heatmap list标题
ht1 = Heatmap(mat1, name = "ht1", row_title = "Heatmap 1", column_title = "Heatmap 1")
ht2 = Heatmap(mat2, name = "ht2", row_title = "Heatmap 2", column_title = "Heatmap 2")
ht_list = ht1 + ht2
draw(ht_list, row_title = "Two heatmaps, row title", row_title_gp = gpar(col = "red"),
column_title = "Two heatmaps, column title", column_title_side = "bottom")
heatmap list标题
Gaps between heatmaps 热图间的间隔
热图间的间隔可以通过 gap 参数配合unit 对象来设置.
draw(ht_list, gap = unit(1, "cm"))
热图间的间隔距离设置
draw(ht_list + ht_list, gap = unit(c(3, 6, 9, 0), "mm"))
## Warning in .local(object, ...): Heatmap/row annotation names are duplicated: ht1, ht2
image.png
Size of heatmaps 热图的大小设置
一些(不是所有)热图的宽度可以设置为固定的宽度。
ht1 = Heatmap(mat1, name = "ht1", column_title = "Heatmap 1")
ht2 = Heatmap(mat2, name = "ht2", column_title = "Heatmap 2", width = unit(5, "cm"))
ht1 + ht2
为热图设置固定宽度
or宽度可以设置为相对值。 Please not in this case, width for all heatmaps should be set (relative width and fixed width can be mixed)
ht1 = Heatmap(mat1, name = "ht1", column_title = "Heatmap 1", width = 2)
ht2 = Heatmap(mat2, name = "ht2", column_title = "Heatmap 2", width = 1)
ht1 + ht2
为热图设置相对宽度
Auto adjustment 自动调整
如果绘制了多个热图，则会有一些自动调整。应该有一个主热图，默认情况下是第一个热图。在剩余热图中的一些设置将会被主热图的设置所修改 The adjustment are:
- 剩余热图的行聚类被移除.
- 剩余热图的行标题被移除.
- 如果主热图被按行分隔，其他剩余热图也将被拆分，拆分样式和主热图一样.
主热图可以通过“main_heatmap”参数指定。它的值可以是 a numeric index或热图的名称(当然，在创建“热图”对象时需要设置热图名称).
ht1 = Heatmap(mat1, name = "ht1", column_title = "Heatmap 1", km = 2)
ht2 = Heatmap(mat2, name = "ht2", column_title = "Heatmap 2")
ht1 + ht2
为热图设置title
# note we changed the order of `ht1` and `ht2`
draw(ht2 + ht1)
调换两个热图的顺序
# here although `ht1` is the second heatmap, we specify `ht1` to be
# the main heatmap by explicitely setting `main_heatmap` argument
draw(ht2 + ht1, main_heatmap = "ht1")
#用main_heatmap参数设定主热图
设置主热图
如果主热图中没有行聚类，则所有其他热图也没有行聚类
ht1 = Heatmap(mat1, name = "ht1", column_title = "Heatmap 1", cluster_rows = FALSE)
ht2 = Heatmap(mat2, name = "ht2", column_title = "Heatmap 2")
ht1 + ht2
主热图不设行聚类
Change graphic parameters simultaneously 同时更改图形参数
ht_global_opt() can set graphic parameters for dimension names and titles as global settings.ht_global_opt()可以为维名称和标题设置图形参数，将其设置为全局设置。
ht_global_opt(heatmap_row_names_gp = gpar(fontface = "italic"),
heatmap_column_names_gp = gpar(fontsize = 14))
ht1 = Heatmap(mat1, name = "ht1", column_title = "Heatmap 1")
ht2 = Heatmap(mat2, name = "ht2", column_title = "Heatmap 2")
ht1 + ht2
全局设置
ht_global_opt(RESET = TRUE)
以下是“ht_global_opt()”支持的全局设置。通过这个函数，您还可以控制图例的设置.
names(ht_global_opt())
## [1] "heatmap_row_names_gp" "heatmap_column_names_gp"
## [3] "heatmap_row_title_gp" "heatmap_column_title_gp"
## [5] "heatmap_legend_title_gp" "heatmap_legend_title_position"
## [7] "heatmap_legend_labels_gp" "heatmap_legend_grid_height"
## [9] "heatmap_legend_grid_width" "heatmap_legend_grid_border"
## [11] "annotation_legend_title_gp" "annotation_legend_title_position"
## [13] "annotation_legend_labels_gp" "annotation_legend_grid_height"
## [15] "annotation_legend_grid_width" "annotation_legend_grid_border"
## [17] "fast_hclust"
Retrieve orders and dendrograms 检索顺序和树状图
row_order, column_order, row_dend and column_dend 可以被用作从热图中检索相应的信息. 用法可以直接从下方的例子中学习:
ht_list = ht1 + ht2
row_order(ht_list)
## [[1]]
## [1] 8 3 4 1 5 7 2 6 9 11 10 12
column_order(ht_list)
## $ht1
## [1] 5 1 3 2 7 9 6 10 8 4
##
## $ht2
## [1] 9 4 6 7 8 1 5 10 3 2
row_dend(ht_list)
## [[1]]
## 'dendrogram' with 2 branches and 12 members total, at height 16.14288
column_dend(ht_list)
## $ht1
## 'dendrogram' with 2 branches and 10 members total, at height 8.069474
##
## $ht2
## 'dendrogram' with 2 branches and 10 members total, at height 6.883646
如果尚未绘制“ht_list”，那么如果矩阵很大，调用这四个函数会有点慢。但是，如果已经绘制了“ht_list”，这意味着已经将聚类应用于矩阵，那么检索这些信息将非常快。
ht_list = draw(ht1 + ht2)
row_order(ht_list)
column_order(ht_list)
row_dend(ht_list)
column_dend(ht_list)
Heatmap list with row annotations 带有行注释的热图列表(Heatmap list)
行注释可以添加到 heatmap list中, 查看 [Heatmap Annotation] 获取更多的解释.
Modify row orders/clustering in main heatmap 修改主热图中的行顺序/聚类
从版本1.11.1, 主热图的行顺序/聚类设置可以直接在"draw()"函数中设置。这使得切换主热图非常方便，无需单独修改热图中的设置。实际上，在'draw()'中指定的设置将覆盖主热图中的相应设置。
split = rep(c("a", "b"), each = 6)
ht_list = Heatmap(mat1, name = "mat1", cluster_rows = FALSE, column_title = "mat1") +
Heatmap(mat2, name = "mat2", cluster_rows = FALSE, column_title = "mat2")
draw(ht_list, main_heatmap = "mat1", split = split)
image.png
draw(ht_list, main_heatmap = "mat2", km = 2, cluster_rows = TRUE)
image.png
draw(ht_list, cluster_rows = TRUE, main_heatmap = "mat1", show_row_dend =TRUE)
image.png
draw(ht_list, cluster_rows = TRUE, main_heatmap = "mat2", show_row_dend =TRUE)
image.png
Session info
sessionInfo()
## R version 3.5.1 Patched (2018-07-24 r75008)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows Server 2012 R2 x64 (build 9600)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=C LC_CTYPE=English_United States.1252
## [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
## [5] LC_TIME=English_United States.1252
##
## attached base packages:
## [1] stats4 parallel grid stats graphics grDevices utils datasets methods
## [10] base
##
## other attached packages:
## [1] dendextend_1.9.0 dendsort_0.3.3 cluster_2.0.7-1 IRanges_2.16.0
## [5] S4Vectors_0.20.0 BiocGenerics_0.28.0 HilbertCurve_1.12.0 circlize_0.4.4
## [9] ComplexHeatmap_1.20.0 knitr_1.20 markdown_0.8
##
## loaded via a namespace (and not attached):
## [1] mclust_5.4.1 Rcpp_0.12.19 mvtnorm_1.0-8 lattice_0.20-35
## [5] png_0.1-7 class_7.3-14 assertthat_0.2.0 mime_0.6
## [9] R6_2.3.0 GenomeInfoDb_1.18.0 plyr_1.8.4 evaluate_0.12
## [13] ggplot2_3.1.0 highr_0.7 pillar_1.3.0 GlobalOptions_0.1.0
## [17] zlibbioc_1.28.0 rlang_0.3.0.1 lazyeval_0.2.1 diptest_0.75-7
## [21] kernlab_0.9-27 whisker_0.3-2 GetoptLong_0.1.7 stringr_1.3.1
## [25] RCurl_1.95-4.11 munsell_0.5.0 compiler_3.5.1 pkgconfig_2.0.2
## [29] shape_1.4.4 nnet_7.3-12 tidyselect_0.2.5 gridExtra_2.3
## [33] tibble_1.4.2 GenomeInfoDbData_1.2.0 viridisLite_0.3.0 crayon_1.3.4
## [37] dplyr_0.7.7 MASS_7.3-51 bitops_1.0-6 gtable_0.2.0
## [41] magrittr_1.5 scales_1.0.0 stringi_1.2.4 XVector_0.22.0
## [45] viridis_0.5.1 flexmix_2.3-14 bindrcpp_0.2.2 robustbase_0.93-3
## [49] fastcluster_1.1.25 HilbertVis_1.40.0 rjson_0.2.20 RColorBrewer_1.1-2
## [53] tools_3.5.1 fpc_2.1-11.1 glue_1.3.0 trimcluster_0.1-2.1
## [57] DEoptimR_1.0-8 purrr_0.2.5 colorspace_1.3-2 GenomicRanges_1.34.0
## [61] prabclus_2.2-6 bindr_0.1.1 modeltools_0.2-22
