# 使用默认设置生成热图 plotHeatmap -m matrix.gz -out ExampleHeatmap.png # 自定义颜色映射、zMin 和 zMax,并进行 k-means 聚类 plotHeatmap -m matrix_two_groups.gz -out ExampleHeatmap2.png --colorMap RdBu --zMin -3 --zMax 3 --kmeans 4 # 不显示热图周围的框,并自定义颜色列表和 DPI ...
As mentioned above, plotHeatmap has many options, including the ability to do k-means clustering and change the color map. $ plotHeatmap -m matrix_two_groups.gz \ -out ExampleHeatmap2.png \ --colorMap Spectral \ --kmeans 5 \ --plotTitle "Test data with k-means clustering" Tip Mor...
The example below shows clustering by both k means as well as hierarchical clustering. I hope this helps! library(ComplexHeatmap) library(ggplot2) library(dplyr) library(RColorBrewer) library(circlize) library(monocle3) modulated_genes <- graph_test(cds, neighbor_graph = "principal_graph", ...
1.比较分支聚类:我们可以使用不同的聚类算法,比如层次聚类或k-means聚类,来对基因和样本进行聚类分析。这样,我们可以找到具有相似表达模式的基因或样本群集。比较不同分支之间的聚类情况可以帮助我们寻找具有相似功能或相似受调控机制的基因簇。 2.富集分析:基于plot_genes_branched_heatmap中的数据,我们可以进行富集分析...
常见的参数包括聚类算法(如层次聚类、K-means聚类等)、颜色映射方案、分支结构展示方式等。用户可以根据自己的数据特点和分析目的进行设置。 3.结果可视化: 通过调用plot_genes_branched_heatmap函数,并传入数据矩阵和参数配置,即可得到分支热图的可视化结果。结果通常呈现为一个彩色矩阵,行代表基因,列代表样本,颜色表示...
ivokweecommentedMay 21, 2020 Hi. In the deepTools module, it would be nice to include plotHeatmap inside the pipeline as the computeMatrix is already calculated. Thanks. Ivo drpatelhadded thefeature-requestRequest to add new functionalitylabelMay 30, 2020...
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As mentioned above, plotHeatmap has many options, including the ability to do k-means clustering and change the color map. $ plotHeatmap -m matrix_two_groups.gz \ -out ExampleHeatmap2.png \ --colorMap Spectral \ --kmeans 5 \ --plotTitle "Test data with k-means clustering" Tip ...