如何在 R 中将多个树状图与热图合并？

Question

我试图用样本树状图制作热图和层次聚类。

我正在尝试遵循 StackOverflow 中的这个特定线程（合并多个 hclust 对象（或树状图））

我有一个很大的数据框，

    head(joined_df_sorted)
# A tibble: 6 × 24
  chrom   start     end EE85756 EE85757 EE85770 EE85775 EE85784 EE87786 EE87787 EE87788 EE87789 EE87790 EE87811 EE87812 EE87813 EE87814 EE87815 EE87893 EE87894 EE87895 EE87896 EE87897
  <chr>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
1 chr1  1000001 2000000       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3
2 chr1  3000001 4000000       3       4       3       3       3       8       3       3       3       3       3       3       3       3       3       3       3       3       3       3
3 chr1  4000001 5000000       3       4       3       3       3      13       3       3       8       3       3       3       3       3       6       3       3       3       3       3
4 chr1  5000001 6000000       3       4       3       3       3      10       3       3       7       3       3       3       3       3       3       3       3       3       3       3
5 chr1  6000001 7000000       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3
6 chr1  7000001 8000000       3       4       3       3       3       7       3       3       3       3       3       3       3       3       3       3       3       3       3       3
# ℹ 1 more variable: chromid <chr>

到目前为止我所做的是，

    #Joining first 2 columns for making unique row name
    joined_df_sorted$chromid <- paste0(joined_df_sorted$chrom, "_", joined_df_sorted$start)

#Keeping only required columns
joined_df_sorted2 <- as.data.frame(joined_df_sorted[,c(24,4:23)])


#making first column as row name
joined_df_sorted3<-joined_df_sorted2
joined_df_sorted3X <- joined_df_sorted3[,-1]
rownames(joined_df_sorted3X) <- joined_df_sorted3[,1]

## transposing the dataframe without changing datatype
install.packages("sjmisc")
library(sjmisc)

joined_df_sorted3X_t<-joined_df_sorted3X %>% 
  rotate_df(cn = FALSE)

CanCohortDat<-joined_df_sorted3X_t

BileDuct  <- c("EE87786",   "EE87787",  "EE87788",  "EE87789",  "EE87790")
Breast <-  c("EE87811", "EE87812",  "EE87813",  "EE87814",  "EE87815")
Gastric <- c("EE87893", "EE87894",  "EE87895",  "EE87896",  "EE87897")
Healthy <- c("EE85756", "EE85757",  "EE85770","EE85775",    "EE85784")

#Separate clustering of 4 distinct datasource
h1 <- hclust(dist(CanCohortDat[BileDuct,]))
h2 <- hclust(dist(CanCohortDat[Breast,]))
h3 <- hclust(dist(CanCohortDat[Gastric,]))
h4 <- hclust(dist(CanCohortDat[Healthy,]))

#merge 4 clusters
hc <- as.hclust(merge(merge(merge(
  as.dendrogram(h1), as.dendrogram(h2)), as.dendrogram(h3)), 
  as.dendrogram(h4)))

CanCoh <-CanCohortDat[c(BileDuct, Breast, Gastric, Healthy),]


cohort_annotation <- data.frame(Region = c(rep("BileDuct", length(BileDuct)), 
                                           rep("Breast", length(Breast)),
                                           rep("Gastric", length(Gastric)),
                                           rep("Healthy", length(Healthy))),
                                row.names = c(BileDuct, Breast, Gastric, Healthy))


#Heatmap
pheatmap(CanCoh , cluster_rows = hc, 
         annotation_row = cohort_annotation)


#############ERROR##############
`use_raster` is automatically set to TRUE for a matrix with more than 2000
columns You can control `use_raster` argument by explicitly setting TRUE/FALSE
to it.

Set `ht_opt$message = FALSE` to turn off this message.
'magick' package is suggested to install to give better rasterization.

Set `ht_opt$message = FALSE` to turn off this message.
Error in hclust(get_dist(t(submat), distance), method = method) : 
  NA/NaN/Inf in foreign function call (arg 10)
In addition: Warning message:
The input is a data frame, convert it to the matrix. 

我的输出应如下所示：EE* 是应位于 y 轴并按合并树状图分组的不同样本，x 轴应显示染色体位置。

Answer 1

您使用的看起来像包

ComplexHeatmap

（来自错误消息）？据我所知，当您按组变量拆分时，

ComplexHeamtap

可以自动合并 heamtap 树状图。详情请参阅：https://jokergoo.github.io/ComplexHeatmap-reference/book/a-single-heatmap.html#split-by-categorical-variables.

您不必自己合并树状图。

问题是你的矩阵出了问题（可能缺失值太多），一些与你类似的问题已经在github上被问到了：

• https://github.com/jokergoo/ComplexHeatmap/issues/155
• https://github.com/jokergoo/ComplexHeatmap/issues/938