From c4fe1fc08a2a95f09ee5c92548849d703ace5c8b Mon Sep 17 00:00:00 2001 From: yun Date: Thu, 11 Jul 2024 15:13:09 +0800 Subject: [PATCH] add chinese document --- README.Rmd | 2 + README.html | 1 + README.md | 3 + README.zh-cn.md | 861 ++++++++++++++++++++++++++++++++++++++++++++++++ 4 files changed, 867 insertions(+) create mode 100644 README.zh-cn.md diff --git a/README.Rmd b/README.Rmd index de7538b..a5b098b 100644 --- a/README.Rmd +++ b/README.Rmd @@ -21,5 +21,7 @@ knitr::opts_chunk$set( [![R-CMD-check](https://github.com/Yunuuuu/eheat/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Yunuuuu/eheat/actions/workflows/R-CMD-check.yaml) +*Read this in other languages: [English](README.md), [简体中文](README.zh-cn.md)* + ```{r child = "vignettes/eheat.Rmd"} ``` diff --git a/README.html b/README.html index c471e39..95f73db 100644 --- a/README.html +++ b/README.html @@ -620,6 +620,7 @@

eheat

R-CMD-check

+

Read this in other languages: English, 简体中文

This package serves as a bridge between the ggplot2 and ComplexHeatmap packages. Essentially, all ggplot2 geometries and operations can be utilized in ComplexHeatmap through the eheat package, with diff --git a/README.md b/README.md index 8b3ac4d..d7fc1f7 100644 --- a/README.md +++ b/README.md @@ -15,6 +15,9 @@ [![R-CMD-check](https://github.com/Yunuuuu/eheat/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Yunuuuu/eheat/actions/workflows/R-CMD-check.yaml) +*Read this in other languages: [English](README.md), +[简体中文](README.zh-cn.md)* + This package serves as a bridge between the [ggplot2](https://ggplot2.tidyverse.org/) and [ComplexHeatmap](https://github.com/jokergoo/ComplexHeatmap) packages. diff --git a/README.zh-cn.md b/README.zh-cn.md new file mode 100644 index 0000000..428d4de --- /dev/null +++ b/README.zh-cn.md @@ -0,0 +1,861 @@ +由chatgpt-3.5翻译 + +- [eheat](#eheat) + - [安装](#安装) + - [`ggheat`](#ggheat) + - [`gganno`](#gganno) + - [`anno_gg` 和 `anno_gg2`](#anno_gg-和-anno_gg2) + - [会话信息](#会话信息) + + + +# eheat + + + +[![R-CMD-check](https://github.com/Yunuuuu/eheat/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Yunuuuu/eheat/actions/workflows/R-CMD-check.yaml) + + +*在其他语言中阅读：[English](README.md), +[简体中文](README.zh-cn.md)* + +这个包用作 [ggplot2](https://ggplot2.tidyverse.org/) 和 +[ComplexHeatmap](https://github.com/jokergoo/ComplexHeatmap) 之间的桥梁。 +基本上，通过 `eheat` 包，可以利用所有的 ggplot2 几何形状和操作在 ComplexHeatmap 中运用，除了面板操作（不应该在 `eheat` 包中进行）。幸运的是，ComplexHeatmap 能够独立处理这些操作，因此它们是不必要的。 + +## 安装 + +您可以使用以下代码从 [GitHub](https://github.com/) 安装 `eheat` 的开发版本： + +``` r +if (!requireNamespace("pak")) { + install.packages("pak", + repos = sprintf( + "https://r-lib.github.io/p/pak/devel/%s/%s/%s", + .Platform$pkgType, R.Version()$os, R.Version()$arch + ) + ) +} +pak::pkg_install("Yunuuuu/eheat") +``` + +``` r +library(eheat) +#> Loading required package: ComplexHeatmap +#> Loading required package: grid +#> ======================================== +#> ComplexHeatmap version 2.20.0 +#> Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/ +#> Github page: https://github.com/jokergoo/ComplexHeatmap +#> Documentation: http://jokergoo.github.io/ComplexHeatmap-reference +#> +#> If you use it in published research, please cite either one: +#> - Gu, Z. Complex Heatmap Visualization. iMeta 2022. +#> - Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional +#> genomic data. Bioinformatics 2016. +#> +#> +#> The new InteractiveComplexHeatmap package can directly export static +#> complex heatmaps into an interactive Shiny app with zero effort. Have a try! +#> +#> This message can be suppressed by: +#> suppressPackageStartupMessages(library(ComplexHeatmap)) +#> ======================================== +#> Loading required package: ggplot2 +``` + +让我们从创建一些示例数据开始，以下代码直接从 ComplexHeatmap 书中复制： + +``` r +set.seed(123) +nr1 <- 4 +nr2 <- 8 +nr3 <- 6 +nr <- nr1 + nr2 + nr3 +nc1 <- 6 +nc2 <- 8 +nc3 <- 10 +nc <- nc1 + nc2 + nc3 +mat <- cbind( + rbind( + matrix(rnorm(nr1 * nc1, mean = 1, sd = 0.5), nrow = nr1), + matrix(rnorm(nr2 * nc1, mean = 0, sd = 0.5), nrow = nr2), + matrix(rnorm(nr3 * nc1, mean = 0, sd = 0.5), nrow = nr3) + ), + rbind( + matrix(rnorm(nr1 * nc2, mean = 0, sd = 0.5), nrow = nr1), + matrix(rnorm(nr2 * nc2, mean = 1, sd = 0.5), nrow = nr2), + matrix(rnorm(nr3 * nc2, mean = 0, sd = 0.5), nrow = nr3) + ), + rbind( + matrix(rnorm(nr1 * nc3, mean = 0.5, sd = 0.5), nrow = nr1), + matrix(rnorm(nr2 * nc3, mean = 0.5, sd = 0.5), nrow = nr2), + matrix(rnorm(nr3 * nc3, mean = 1, sd = 0.5), nrow = nr3) + ) +) +mat <- mat[sample(nr, nr), sample(nc, nc)] # 随机重排行和列的顺序 +rownames(mat) <- paste0("第", seq_len(nr), "行") +colnames(mat) <- paste0("第", seq_len(nc), "列") +small_mat <- mat[1:9, 1:9] +``` + +`eheat` 包的核心函数是 `ggheat` 和 `gganno`。这两个函数包含了所有必要的功能。`ggheat` 作为 `ComplexHeatmap::Heatmap` 函数的替代，而 `gganno` 则替换了 ComplexHeatmap 包中的所有 `anno_*` 函数，为我们的要求提供了一个全面的解决方案。在 ComplexHeatmap 中使用 ggplot2 的一个重要优势是绘制统计注释的简易性。另一个好处是图例可以直接从 ggplot2 图中提取，省去了手动添加图例的步骤。 + +## `ggheat` + +使用 `ggheat`，创建一个简单的热图很容易。默认的颜色映射在 ComplexHeatmap 和 ggplot2 之间不一致。 + +``` r +draw(ggheat(small_mat)) +``` + + + +您不需要显式指定颜色映射，因为您可以直接使用 ggplot2 中的 `scale_*` 函数。所有导航图例都将直接从 `ggplot2` 中提取。`ggheat` 的关键参数是 `ggfn`，它接受一个 ggplot2 对象，该对象具有由 `ggplot(data, aes(.data$x, .data$y))` 创建的默认数据和映射。数据包含以下列： + +- `.slice`：切片编号，由 `.slice_row` 和 `.slice_column` 组合而成。 + +- `.slice_row`：切片的行号 + +- `.slice_column`：切片的列号 + +- `.row_names` 和 `.column_names`：原始矩阵的行和列名称（仅当存在名称时适用）。 + +- `.row_index` 和 `.column_index`：原始矩阵的行和列索引。 + +- `x` 和 `y`：`x` 和 `y` 坐标 + +- `value`：热图矩阵的实际值。 + +## 翻译 private_upload/2024-07-11-07-09-27/README.md.part-1.md + +这是一个Markdown文件，请将其翻译成中文，不要修改任何现有的Markdown命令： + +``` r +pdf(NULL) +draw(ggheat(small_mat, function(x) { + print(head(x$data)) + x +})) +#> .slice .slice_row .slice_column .row_names .column_names .row_index +#> 1 r1c1 1 1 row1 column1 1 +#> 2 r1c1 1 1 row1 column2 1 +#> 3 r1c1 1 1 row1 column3 1 +#> 4 r1c1 1 1 row1 column4 1 +#> 5 r1c1 1 1 row1 column5 1 +#> 6 r1c1 1 1 row1 column6 1 +#> .column_index x y value +#> 1 1 1 2 0.9047416 +#> 2 2 8 2 -0.3522982 +#> 3 3 6 2 0.5016096 +#> 4 4 2 2 1.2676994 +#> 5 5 3 2 0.8251229 +#> 6 6 7 2 0.1621522 +``` + +``` r +dev.off() +#> png +#> 2 +``` + +ggplot2中的`scale_*`函数的丰富性使得修改颜色映射变得很容易。 + +``` r +draw(ggheat(small_mat, function(p) { + # 将使用零作为中点 + p + scale_fill_gradient2() +})) +``` + + + +``` r +draw(ggheat(small_mat, function(p) { + p + scale_fill_viridis_c(option = "magma") +})) +``` + + + +图例可以通过ggplot2中的`guide_*`函数进行控制。 + +``` r +draw(ggheat(small_mat, function(p) { + p + scale_fill_viridis_c(guide = guide_colorbar(direction = "horizontal")) +})) +``` + + + +您可以添加更多的几何对象。 + +``` r +draw( + ggheat(small_mat, function(p) { + p + + geom_text(aes(label = sprintf("%d * %d", .row_index, .column_index))) + }) +) +``` + + + +您也可以使用ComplexHeatmap中的相同方法，通过设置`rect_gp = gpar(type = "none")`来防止内部矩形填充。聚类仍然应用于热图，但在热图正文上没有绘制任何内容。 + +``` r +draw(ggheat(small_mat, rect_gp = gpar(type = "none"))) +``` + + + +请注意，ggplot2和ComplexHeatmap之间的背景不同。然而，ggplot2中的主题系统使得修改和自定义背景变得容易。 + +``` r +draw( + ggheat(small_mat, function(p) { + p + + geom_text(aes(label = sprintf("%d * %d", .row_index, .column_index))) + + theme_bw() + }, rect_gp = gpar(type = "none")) +) +``` + + + +您可以轻松使用`geom_tile`自定义热图填充。 + +``` r +draw( + ggheat(small_mat, function(p) { + p + + geom_tile( + aes(fill = value), + width = 1L, height = 1L, + data = ~ dplyr::filter(.x, y <= x) + ) + + geom_text( + aes(label = sprintf("%d * %d", .row_index, .column_index)), + data = ~ dplyr::filter(.x, y >= x) + ) + + theme_bw() + }, rect_gp = gpar(type = "none")) +) +``` + + + +可以直接使用`ComplexHeatmap::Heatmap`函数的所有功能。 + +``` r +draw(ggheat(small_mat, function(p) { + p + scale_fill_viridis_c() +}, column_km = 2L)) +``` + + + +``` r +draw(ggheat(small_mat, function(p) { + p + scale_fill_viridis_c() +}, column_km = 2L, row_km = 3)) +``` + + + +``` r +draw(ggheat(small_mat, function(p) { + p + + geom_text(aes(label = sprintf("%d * %d", .row_index, .column_index))) + + scale_fill_viridis_c() +}, column_km = 2L, row_km = 3)) +``` + + + +我们可以将ComplexHeatmap中的`layer_fun`或`cell_fun`与`ggfn`结合使用 + +``` r +draw( + ggheat(small_mat, + layer_fun = function(...) { + grid.rect(gp = gpar(lwd = 2, fill = "transparent", col = "red")) + }, column_km = 2L, row_km = 3 + ) +) +``` + + + +`ggheat`仅接管热图正文和图例。行名称和列名称由`ComplexHeatmap::Heatmap`函数控制。 + +``` r +draw(ggheat(small_mat, function(p) { + p + scale_fill_viridis_c() +}, column_km = 2L, row_km = 3, row_names_gp = gpar(col = "red"))) +``` + + + +尽管图例由`ggplot2`控制，但默认图例名称取自`ComplexHeatmap::Heatmap`，以确保保持一致。 + +## 翻译 private_upload/2024-07-11-07-09-27/README.md.part-2.md + +``` r +pdf(NULL) +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = sample(seq_len(nrow(small_mat)), nrow(small_mat), replace = TRUE), + function(p) { + print(head(p$data)) + p + } + ), which = "column" + ) +)) +#> .slice .row_index x value +#> 1 1 1 1 1 +#> 2 1 1 2 1 +#> 3 1 2 1 2 +#> 4 1 2 2 2 +#> 5 1 3 1 3 +#> 6 1 3 2 3 +``` + +``` r +dev.off() +#> png +#> 2 +``` + +## 翻译 private_upload/2024-07-11-07-09-27/README.md.part-3.md + +这是一个Markdown文件，请将其翻译成中文，不要修改任何现有的Markdown命令： + +``` r +pdf(NULL) +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = sample(1:10, nrow(small_mat)), + function(p) { + print(head(p$data)) + p + } + ), which = "column" + ) +)) +#> ℹ 将简单向量转换为单列矩阵 +#> .slice .column_names .row_index .column_index x value +#> 1 1 V1 1 1 1 9 +#> 2 1 V1 2 1 8 3 +#> 3 1 V1 3 1 6 1 +#> 4 1 V1 4 1 2 10 +#> 5 1 V1 5 1 3 7 +#> 6 1 V1 6 1 7 6 +``` + +``` r +dev.off() +#> png +#> 2 +``` + +如果没有提供数据，则将使用热图矩阵，相同的原则适用于矩阵（重新整形为长格式数据框）。注意：对于列注释，热图矩阵将被转置，因为 `gganno` 总是将行视为观测值。 + +``` r +pdf(NULL) +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = NULL, + function(p) { + print(head(p$data)) + p + } + ), which = "column" + ) +)) +#> .slice .row_names .column_names .row_index .column_index x value +#> 1 1 column1 row1 1 1 1 0.90474160 +#> 2 1 column1 row2 1 2 1 0.90882972 +#> 3 1 column1 row3 1 3 1 0.28074668 +#> 4 1 column1 row4 1 4 1 0.02729558 +#> 5 1 column1 row5 1 5 1 -0.32552445 +#> 6 1 column1 row6 1 6 1 0.58403269 +``` + +``` r +dev.off() +#> png +#> 2 +``` + +``` r +pdf(NULL) +draw(ggheat(small_mat, + left_annotation = HeatmapAnnotation( + foo = gganno( + data = NULL, + function(p) { + print(head(p$data)) + p + } + ), + which = "row" + ) +)) +#> .slice .row_names .column_names .row_index .column_index y value +#> 1 1 row1 column6 1 6 2 0.1621522 +#> 2 1 row1 column9 1 9 2 -0.1629658 +#> 3 1 row1 column1 1 1 2 0.9047416 +#> 4 1 row1 column7 1 7 2 -0.2869867 +#> 5 1 row1 column8 1 8 2 0.6803262 +#> 6 1 row1 column4 1 4 2 1.2676994 +``` + +``` r +dev.off() +#> png +#> 2 +``` + +您还可以在数据中提供一个函数（也可以使用 `purrr-lambda`），该函数将在热图矩阵中应用。注意：对于列注释，在将热图矩阵传递给此函数之前，矩阵将被转置。 + +``` r +pdf(NULL) +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = function(x) { + if (identical(x, small_mat)) { + print("矩阵未转置") + } else if (identical(x, t(small_mat))) { + print("矩阵已转置") + } + rowSums(x) + } + ), + which = "column" + ) +)) +#> [1] "矩阵已转置" +#> ℹ 将简单向量转换为单列矩阵 +``` + +``` r +dev.off() +#> png +#> 2 +``` + +``` r +pdf(NULL) +draw(ggheat(small_mat, + left_annotation = HeatmapAnnotation( + foo = gganno( + data = function(x) { + if (identical(x, small_mat)) { + print("矩阵未转置") + } else if (identical(x, t(small_mat))) { + print("矩阵已转置") + } + rowSums(x) + } + ), + which = "row" + ) +)) +#> [1] "矩阵未转置" +#> ℹ 将简单向量转换为单列矩阵 +``` + +``` r +dev.off() +#> png +#> 2 +``` + +类似地，我们可以利用ggplot2中提供的几何对象（geoms）在ggfn中创建注释。 + +``` r +anno_data <- sample(1:10, nrow(small_mat)) +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = anno_data, + function(p) { + p + geom_point(aes(x, value)) + } + ), which = "column" + ) +)) +#> ℹ 将简单向量转换为单列矩阵 +``` + + + +图例也将被提取，类似地传递给 `annotation_legend_list` 参数。 + +## 翻译 private_upload/2024-07-11-07-09-27/README.md.part-4.md + +``` r +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = anno_data, + function(p) { + p + geom_bar(aes(y = value, fill = factor(.row_index)), stat = "identity") + }, height = unit(5, "cm") + ), which = "column" + ) +), merge_legends = TRUE) +#> ℹ 将简单向量转换为单列矩阵 +``` + + + +``` r +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = anno_data, + function(p) { + p + geom_boxplot(aes(y = value, fill = factor(.slice))) + }, height = unit(5, "cm") + ), which = "column" + ), column_km = 2L +), merge_legends = TRUE) +#> ℹ 将简单向量转换为单列矩阵 +``` + + + +``` r +box_matrix1 <- matrix(rnorm(ncol(small_mat)^2L, 10), nrow = ncol(small_mat)) +colnames(box_matrix1) <- rep_len("group1", ncol(small_mat)) +box_matrix2 <- matrix(rnorm(ncol(small_mat)^2L, 20), nrow = ncol(small_mat)) +colnames(box_matrix2) <- rep_len("group2", ncol(small_mat)) +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = cbind(box_matrix1, box_matrix2), + function(p) { + p + + geom_violin( + aes( + y = value, fill = factor(.column_names), + color = factor(.slice), + group = paste(.slice, .row_index, .column_names, sep = "-") + ) + ) + + geom_boxplot( + aes( + y = value, fill = factor(.column_names), + color = factor(.slice), + group = paste(.slice, .row_index, .column_names, sep = "-") + ), + width = 0.2, + position = position_dodge(width = 0.9) + ) + + scale_fill_brewer( + name = "组别", type = "qual", palette = "Set3" + ) + + scale_color_brewer( + name = "切片", type = "qual", palette = "Set1" + ) + }, height = unit(3, "cm") + ), which = "column" + ), column_km = 2L +), merge_legends = TRUE) +``` + + + +``` r +draw(ggheat(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = anno_data, + function(p) { + p + aes(y = value) + geom_text(aes(label = .row_index)) + }, height = unit(2, "cm") + ), which = "column" + ), + bottom_annotation = HeatmapAnnotation( + foo = gganno( + function(p) { + p + aes(y = value) + + geom_text(aes(label = .row_index)) + + scale_y_reverse() + }, + data = anno_data, + which = "column", height = unit(2, "cm") + ), + which = "column" + ), + right_annotation = HeatmapAnnotation( + foo = gganno( + function(p) { + p + aes(x = value) + + geom_text(aes(label = .row_index)) + }, + data = anno_data, + width = unit(3, "cm") + ), + which = "row" + ), + left_annotation = HeatmapAnnotation( + foo = gganno( + function(p) { + p + aes(x = value) + + geom_text(aes(label = .row_index)) + + scale_x_reverse() + }, + data = anno_data, + width = unit(3, "cm") + ), + which = "row" + ), + row_km = 2L, column_km = 2L, +), merge_legends = TRUE) +#> ℹ 将简单向量转换为单列矩阵 +#> ℹ 将简单向量转换为单列矩阵 +#> ℹ 将简单向量转换为单列矩阵 +#> ℹ 将简单向量转换为单列矩阵 +``` + + + +`gganno`函数可以与`Heatmap`函数一起使用，这样，图例将不会被提取。通常情况下，我们应该只使用`ggheat`和`gganno`。 + +``` r +draw(Heatmap(small_mat, + top_annotation = HeatmapAnnotation( + foo = gganno( + data = anno_data, + function(p) { + p + geom_bar(aes(y = value, fill = factor(.row_index)), stat = "identity") + } + ), which = "column" + ) +), merge_legends = TRUE) +#> ℹ 将简单向量转换为单列矩阵 +``` + + + +## `anno_gg`和`anno_gg2` + +这两个函数的作用与ComplexHeatmap中的其他注释函数类似。它们接受一个ggplot对象，并将其适应ComplexHeatmap注释区域。 + +``` r +g <- ggplot(mpg, aes(displ, hwy, colour = class)) + + geom_point() +m <- matrix(rnorm(100), 10) + +# anno_gg-panel: clip = "off" ------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg(g, "panel", + clip = "off", + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + +## 翻译 private_upload/2024-07-11-07-09-27/README.md.part-5.md + +这是一个Markdown文件，请将其翻译成中文，并且不要修改任何现有的Markdown命令： + +``` + + +``` r +# anno_gg-panel: clip = "on" -------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg(g, "panel", + clip = "on", + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + + + +``` r +# anno_gg-plot -------------------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg(g, "plot", + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + + + +``` r + +# anno_gg-full -------------------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg(g, "full", + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + + + +`anno_gg2` 和 `anno_gg` 是相同的，区别在于它们的参数，它允许对剪辑功能进行更精确的调整。 + +``` r +# anno_gg2-panel: margins = NULL ------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg2(g, "panel", + margins = NULL, + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + + + +``` r +# anno_gg2-panel: margins = "l" -------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg2(g, "panel", + margins = "l", + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + + + +``` r +# anno_gg2-panel: margins = "r" -------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg2(g, "panel", + margins = "r", + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + + + +``` r +# anno_gg2-plot --------------------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg2(g, "plot", + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + + + +``` r +# anno_gg2-full -------------------- +ggheat(m, + top_annotation = HeatmapAnnotation( + ggplot = anno_gg2( + g + guides(colour = guide_legend( + theme = theme( + legend.key.size = unit(1, "mm"), + legend.text = element_text(size = 10), + legend.key.spacing = unit(0, "mm"), + legend.title.position = "bottom", + legend.key = element_blank() + ), + ncol = 2L + )), + align_with = "full", + height = unit(3, "cm"), + show_name = FALSE + ) + ) +) +``` + + + +## Session 信息 +``` + + +## 翻译 private_upload/2024-07-11-07-09-27/README.md.part-6.md + +``` r +sessionInfo() +#> R版本4.4.0（2024年04月24日） +#> 平台：x86_64-pc-linux-gnu +#> 运行于：Ubuntu 24.04 LTS +#> +#> 矩阵乘积：默认设置 +#> BLAS / LAPACK：/usr/lib/x86_64-linux-gnu/libmkl_rt.so；LAPACK版本3.8.0 +#> +#> 区域设置： +#> [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8 +#> [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8 +#> [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C +#> [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C +#> +#> 时区：Asia/Shanghai +#> 时区代码来源：系统（glibc） +#> +#> 已附加的基本包： +#> [1] grid stats graphics grDevices utils datasets methods +#> [8] base +#> +#> 其他已附加的包： +#> [1] eheat_0.99.8 ggplot2_3.5.1 ComplexHeatmap_2.20.0 +#> +#> 通过命名空间加载的包（未附加）： +#> [1] utf8_1.2.4 generics_0.1.3 tidyr_1.3.1 +#> [4] shape_1.4.6.1 digest_0.6.36 magrittr_2.0.3 +#> [7] evaluate_0.24.0 RColorBrewer_1.1-3 iterators_1.0.14 +#> [10] circlize_0.4.16 fastmap_1.2.0 foreach_1.5.2 +#> [13] doParallel_1.0.17 GlobalOptions_0.1.2 purrr_1.0.2 +#> [16] fansi_1.0.6 viridisLite_0.4.2 scales_1.3.0 +#> [19] codetools_0.2-20 cli_3.6.3 rlang_1.1.4 +#> [22] crayon_1.5.3 munsell_0.5.1 withr_3.0.0 +#> [25] yaml_2.3.8 ggh4x_0.2.8 tools_4.4.0 +#> [28] parallel_4.4.0 dplyr_1.1.4 colorspace_2.1-0 +#> [31] GetoptLong_1.0.5 BiocGenerics_0.50.0 vctrs_0.6.5 +#> [34] R6_2.5.1 png_0.1-8 matrixStats_1.3.0 +#> [37] stats4_4.4.0 lifecycle_1.0.4 magick_2.8.3 +#> [40] S4Vectors_0.42.0 IRanges_2.38.0 clue_0.3-65 +#> [43] cluster_2.1.6 pkgconfig_2.0.3 pillar_1.9.0 +#> [46] gtable_0.3.5 glue_1.7.0 Rcpp_1.0.12 +#> [49] highr_0.11 xfun_0.45 tibble_3.2.1 +#> [52] tidyselect_1.2.1 knitr_1.47 farver_2.1.2 +#> [55] rjson_0.2.21 htmltools_0.5.8.1 labeling_0.4.3 +#> [58] rmarkdown_2.27 Cairo_1.6-2 compiler_4.4.0 +``` + +