test–toy
Zhsh006
12/3/2021
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library(pheatmap)
?pheatmap
# Create test matrix
test = matrix(rnorm(200), 20, 10)
test## [,1] [,2] [,3] [,4] [,5] [,6]
## [1,] 1.7720179 -2.2312041 0.0008033192 -0.9366317 1.20319759 0.32057143
## [2,] 0.9424521 -0.2754375 0.1137390976 1.2096740 0.41987282 0.64214789
## [3,] 1.4973987 -1.1307243 0.2604465304 -0.4188725 0.45326260 1.36196244
## [4,] 0.8501888 -0.8845835 0.8271287445 0.6842597 -0.08667241 -0.43180510
## [5,] 0.0531542 1.1030540 0.6447211595 -0.7887825 1.29545924 -1.83661519
## [6,] -1.4008452 -1.3790862 -0.0196172080 -0.9726631 -0.92771199 0.97529388
## [7,] 1.6024032 0.3061658 -0.1803969387 0.2041019 0.59584985 1.00969506
## [8,] -0.1760314 0.7661342 0.5896748525 0.1313049 0.22897116 1.84450921
## [9,] 0.6573316 -0.5888971 -1.6111832291 1.5591689 2.62138415 0.67215805
## [10,] -0.9269316 -0.3591864 -0.5020076730 0.1459360 -0.25402137 0.31351954
## [11,] -0.6973361 -2.1741696 -0.3051690348 1.2746334 0.25285919 2.48917254
## [12,] -0.1099342 1.2963182 0.2678471531 1.3966800 -1.35867564 -0.11753505
## [13,] 0.9160942 -0.9285285 -0.0386133158 2.2530483 0.01620227 0.26088368
## [14,] 0.9591300 0.2151505 0.0324787284 0.4794928 -0.33793071 -0.21605758
## [15,] 0.1389228 -1.4250073 -0.8213879860 0.7838683 -0.27955335 0.73225139
## [16,] -1.1677052 1.2163652 0.5747413403 0.4404896 0.72881284 0.21330741
## [17,] 0.6545647 1.2233523 -1.2557241583 0.7058058 -0.18150514 0.02551105
## [18,] 0.4757077 2.8432732 -0.3472685253 -0.1146986 -0.76792964 -0.35725449
## [19,] 1.1643460 -0.7519785 0.5066130055 0.1553126 -0.16582043 1.48604519
## [20,] 0.3837661 0.3658713 0.8159478959 -0.7941376 0.49802058 0.05265993
## [,7] [,8] [,9] [,10]
## [1,] -1.99620216 -0.58144691 -1.39449519 0.53160450
## [2,] 1.55231261 0.07070202 -1.13067926 0.51877139
## [3,] 0.78524308 -0.05228953 0.35576326 0.43212422
## [4,] 1.74756261 0.19563622 -0.66988810 1.52996246
## [5,] 1.22932663 0.72726560 -0.17160490 -1.44852258
## [6,] -0.28077511 -1.34570388 -0.48839934 -0.29982641
## [7,] -0.78594391 0.08970703 0.60995894 0.11806282
## [8,] 0.25253274 0.68536158 1.49512323 0.44912358
## [9,] -0.26111862 -0.64094770 0.78140770 1.08976444
## [10,] -0.13735012 -0.44924210 -0.66413751 -0.64357195
## [11,] 0.84289802 -0.12967526 0.74890295 -1.75850101
## [12,] 1.16077980 -0.24311960 0.18515907 -0.39796677
## [13,] -1.79345046 0.35133139 1.15967892 -0.02357812
## [14,] 0.08038960 0.22715220 1.53218708 0.40940664
## [15,] 1.13620192 0.68921973 -2.19263207 0.00650299
## [16,] 0.22028965 0.53116547 0.90517980 0.31454274
## [17,] 0.82787218 -0.21817403 -0.01185775 -0.52808237
## [18,] -0.83373060 -1.54174801 -0.04465615 1.81389836
## [19,] -0.09277748 0.19117808 -0.12907990 -2.55805781
## [20,] -1.86354074 -2.20944382 -1.51514298 -0.55388181test[1:10, seq(1, 10, 2)] = test[1:10, seq(1, 10, 2)] + 3
test[11:20, seq(2, 10, 2)] = test[11:20, seq(2, 10, 2)] + 2
test[15:20, seq(2, 10, 2)] = test[15:20, seq(2, 10, 2)] + 4
test## [,1] [,2] [,3] [,4] [,5] [,6]
## [1,] 4.7720179 -2.2312041 3.00080332 -0.9366317 4.20319759 0.3205714
## [2,] 3.9424521 -0.2754375 3.11373910 1.2096740 3.41987282 0.6421479
## [3,] 4.4973987 -1.1307243 3.26044653 -0.4188725 3.45326260 1.3619624
## [4,] 3.8501888 -0.8845835 3.82712874 0.6842597 2.91332759 -0.4318051
## [5,] 3.0531542 1.1030540 3.64472116 -0.7887825 4.29545924 -1.8366152
## [6,] 1.5991548 -1.3790862 2.98038279 -0.9726631 2.07228801 0.9752939
## [7,] 4.6024032 0.3061658 2.81960306 0.2041019 3.59584985 1.0096951
## [8,] 2.8239686 0.7661342 3.58967485 0.1313049 3.22897116 1.8445092
## [9,] 3.6573316 -0.5888971 1.38881677 1.5591689 5.62138415 0.6721580
## [10,] 2.0730684 -0.3591864 2.49799233 0.1459360 2.74597863 0.3135195
## [11,] -0.6973361 -0.1741696 -0.30516903 3.2746334 0.25285919 4.4891725
## [12,] -0.1099342 3.2963182 0.26784715 3.3966800 -1.35867564 1.8824649
## [13,] 0.9160942 1.0714715 -0.03861332 4.2530483 0.01620227 2.2608837
## [14,] 0.9591300 2.2151505 0.03247873 2.4794928 -0.33793071 1.7839424
## [15,] 0.1389228 4.5749927 -0.82138799 6.7838683 -0.27955335 6.7322514
## [16,] -1.1677052 7.2163652 0.57474134 6.4404896 0.72881284 6.2133074
## [17,] 0.6545647 7.2233523 -1.25572416 6.7058058 -0.18150514 6.0255111
## [18,] 0.4757077 8.8432732 -0.34726853 5.8853014 -0.76792964 5.6427455
## [19,] 1.1643460 5.2480215 0.50661301 6.1553126 -0.16582043 7.4860452
## [20,] 0.3837661 6.3658713 0.81594790 5.2058624 0.49802058 6.0526599
## [,7] [,8] [,9] [,10]
## [1,] 1.00379784 -0.58144691 1.60550481 0.5316045
## [2,] 4.55231261 0.07070202 1.86932074 0.5187714
## [3,] 3.78524308 -0.05228953 3.35576326 0.4321242
## [4,] 4.74756261 0.19563622 2.33011190 1.5299625
## [5,] 4.22932663 0.72726560 2.82839510 -1.4485226
## [6,] 2.71922489 -1.34570388 2.51160066 -0.2998264
## [7,] 2.21405609 0.08970703 3.60995894 0.1180628
## [8,] 3.25253274 0.68536158 4.49512323 0.4491236
## [9,] 2.73888138 -0.64094770 3.78140770 1.0897644
## [10,] 2.86264988 -0.44924210 2.33586249 -0.6435719
## [11,] 0.84289802 1.87032474 0.74890295 0.2414990
## [12,] 1.16077980 1.75688040 0.18515907 1.6020332
## [13,] -1.79345046 2.35133139 1.15967892 1.9764219
## [14,] 0.08038960 2.22715220 1.53218708 2.4094066
## [15,] 1.13620192 6.68921973 -2.19263207 6.0065030
## [16,] 0.22028965 6.53116547 0.90517980 6.3145427
## [17,] 0.82787218 5.78182597 -0.01185775 5.4719176
## [18,] -0.83373060 4.45825199 -0.04465615 7.8138984
## [19,] -0.09277748 6.19117808 -0.12907990 3.4419422
## [20,] -1.86354074 3.79055618 -1.51514298 5.4461182colnames(test) = paste("Test", 1:10, sep = "")
rownames(test) = paste("Gene", 1:20, sep = "")画图
pheatmap(test)
pheatmap(test, kmeans_k = 2)
pheatmap(test, scale = "row", clustering_distance_rows = "correlation")
pheatmap(test, color = colorRampPalette(c("navy", "white", "firebrick3"))(50))
pheatmap(test, cluster_row = FALSE)
pheatmap(test, legend = FALSE)
Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.
# install.packages("RColorbrewer")
library(RColorBrewer)
pheatmap(
test,#数据矩阵
color = colorRampPalette(rev(brewer.pal(n = 7, name ="RdYlBu")))(100), #设定图标颜色
kmeans_k = NA, #把一个样本所有的基因分为NA个cluster。NA可以是2，3，4等等，若不写则不聚类。
breaks = NA,
border_color = "grey60",#单元格边框的颜色，如果不绘制单元格边框，则选择NA
cellwidth = NA, #单元格的宽度，如果保留为 NA，则值取决于绘图窗口的大小。
cellheight = NA, #单元格的高度，如果保留为 NA，则值取决于绘图窗口的大小。
scale = "none", #按行“row”，列“column”或者无“none”标准化。
cluster_rows = TRUE,#按行进行hclust聚类
cluster_cols = TRUE, #按列进行hclust聚类
clustering_distance_rows = "correlation",#用于聚类行的距离度量，距离度量有两种：：Pearson相关系数的“correlation"或dist函数包含的距离度量（This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski". ）。
clustering_distance_cols = "euclidean", ##用于聚类列的距离度量，距离度量有两种：：Pearson相关系数的“correlation"或dist函数包含的距离度量（This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski". ）。
clustering_method = "complete",#聚类方法同hclust（This should be (an unambiguous abbreviation of) one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC).）
cutree_rows = NA,#行被划分成的簇数，基于层次聚类（使用cutree），如果行没有聚类，则忽略该参数
cutree_cols = NA,#列被划分成的簇数，基于层次聚类（使用cutree），如果行没有聚类，则忽略该参数
treeheight_row = 50,#行聚类树的高度，默认50
treeheight_col = 50,#列聚类树的高度，默认50
legend = TRUE, #注释标签
legend_breaks = NA,#将legend进行截断，例如只显示legend的前几行
legend_labels = NA, #对上述legend_breaks进行命名，向量
annotation_row = NA, #指定显示在热图左侧的注释的数据框。每行定义特定行的特征。数据和注释中的行使用相应的行名称进行匹配。请注意，配色方案会考虑变量是连续的还是离散的。
annotation_col = NA, #同annotation_row，只不过是针对列的
annotation = NA, #不推荐使用参数
annotation_colors = NA, #手动为annotation_row和annotation_col进行配色的列表
annotation_legend = TRUE, #注释是否画图
annotation_names_row = TRUE, #行注释是否画图
annotation_names_col = TRUE,#列注释是否画图
drop_levels = TRUE, #是否未使用的level也显示在legend中
show_rownames = T,#行名是否显示
show_colnames = T, #列名是否显示
main = NA,#图的标题
fontsize = 10, #绘图基本字体的大小
fontsize_row = 10, #行名的大小，默认与上述fontsize一致
fontsize_col = 10,#列名的大小，默认与上述fontsize一致
angle_col = c("270", "0", "45", "90", "315"), #列标签的角度，只能从（0, 45, 90, 270 and 315）中选。
display_numbers = F, #单元格内是否显示数字
number_format = "%.2f", #单元格中显示的数字的格式字符串。例如，“%.2f”显示 2 个小数位，“%.1e”显示指数表示法（更多信息请参见 sprintf）
number_color = "grey30", #单元格中数字的颜色
fontsize_number = 0.8, #单元格中显示字体的大小
gaps_row = NULL, #将行进行间隙分割，如果已经聚类没法分割，可以进行cutree_rows.
gaps_col = NULL, #同上，进行列的分割。
labels_row = NULL, #用于代替行名的自定义标签
labels_col = NULL, #用于代替列名
filename = NA, #保存图片的文件路径。文件类型由路径中的扩展名决定。目前支持以下格式：png、pdf、tiff、bmp、jpeg。
width = NA, #手动输出文件宽度，英寸为单位
height = NA,#手动输出文件长度，英寸为单位
silent = FALSE, #不绘制图选择TURE。
na_col = "#DDDDDD") #单元格中NA数据的颜色