circos.heatmap()：rowMeans(m)中出错：'x‘必须是至少二维的数组

Question

我正在按照教程来制作circular plots in R。假设我有这样的数据集：

set.seed(123)
    mat1 = rbind(cbind(matrix(rnorm(50*5, mean = 1), nr = 50), 
                   matrix(rnorm(50*5, mean = -1), nr = 50)),
                cbind(matrix(rnorm(50*5, mean = -1), nr = 50), 
                   matrix(rnorm(50*5, mean = 1), nr = 50))
                )
    rownames(mat1) = paste0("R", 1:100)
    colnames(mat1) = paste0("C", 1:10)
    mat1 = mat1[sample(100, 100), ] # randomly permute rows
    split = sample(letters[1:5], 100, replace = TRUE)
    split = factor(split, levels = letters[1:5])

我尝试使用Heatmap，它会相应地返回。

library(ComplexHeatmap)
Heatmap(mat1, row_split = split)

enter image description here

但是，当我尝试使用circos.heatmap()时，它返回错误：

library(circlize)
col_fun1 = colorRamp2(c(-2, 0, 2), c("blue", "white", "red"))
circos.heatmap(mat = mat1, split = split, col = col_fun1)
circos.heatmap(mat = mat1, col = col_fun1)
> Error in rowMeans(m) : 'x' must be an array of at least two dimensions

矩阵本身的维度是100x10。我有没有遗漏什么？

Answer 1

在CRAN版本上也有同样的问题，但是在安装了开发版本之后，这个问题被修正了

devtools::install_github("jokergoo/circlize")

-testing

> library(circlize)
========================================
circlize version 0.4.13
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> col_fun1 = colorRamp2(c(-2, 0, 2), c("blue", "white", "red"))
> ?circos.heatmap
starting httpd help server ... done
> 
> set.seed(123)
> mat1 = rbind(cbind(matrix(rnorm(50*5, mean = 1), nr = 50), 
+                    matrix(rnorm(50*5, mean = -1), nr = 50)),
+              cbind(matrix(rnorm(50*5, mean = -1), nr = 50), 
+                    matrix(rnorm(50*5, mean = 1), nr = 50))
+             )
> rownames(mat1) = paste0("R", 1:100)
> colnames(mat1) = paste0("C", 1:10)
> mat1 = mat1[sample(100, 100), ] # randomly permute rows
> split = sample(letters[1:5], 100, replace = TRUE)
> spilt = factor(split, levels = letters[1:5])
> col_fun1 = colorRamp2(c(-2, 0, 2), c("blue", "white", "red"))
> circos.heatmap(mat1, split = split, col = col_fun1)
> circos.clear()

-output

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