cellphonedbv5受配体多组比较气泡图（原创函数）

前面我们发布了关于cellchat的函数(连夜更新---别说两组了，这个cellchat多组比较气泡图函数10组也能做了)。因为cellchat比较好入手，所以先开刀。很多小伙伴说有没有cpdb的，其实在写函数之初，我们就考虑到了，只不过先从cellchat好入手，本来以为套用可能大差不差，结果cpdb在数据上有很大出入，所以这次费了点时间。However，最终效果刚刚的！

参考：函数B站解说视频（一定要看使用方法哦！）：cellphonedb V5多组受配体分析可视化函数_哔哩哔哩_bilibili

函数主体：也是支持多组，支持自选受配体，自选pathway，自定义分类！

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看看演示：load data

library(ggplot2) library(tidyr) #load data GO_pvals <- read.delim("./GO_cpdb/statistical_analysis_pvalues_08_15_2024_132104.txt", check.names = FALSE) GO_means <- read.delim("./GO_cpdb/statistical_analysis_means_08_15_2024_132104.txt", check.names = FALSE) WT_pvals <- read.delim("./WT_cpdb/statistical_analysis_pvalues_08_15_2024_132617.txt", check.names = FALSE) WT_means <- read.delim("./WT_cpdb/statistical_analysis_means_08_15_2024_132617.txt", check.names = FALSE) data = list(list(pval=GO_pvals, means=GO_means), list(pval=WT_pvals, means=WT_means))

测试1：选定通路

#测试1：cpdb_anno没有pathway，用cpdb默认的，用通路选择 cpdb_interLR <- read.csv(file="cpdb_interLR",header = T) #选定pathway，注释文件中没有pathway ks_cpdb_Group_bubble(cpdb_data = data, group_names = c("GO","WT"), analysis_cells = "Endothelial", pathway = c("Signaling by Transforming growth factor","Signaling by Semaphorin"), cpdb_anno = cpdb_interLR, tag_pos = c(0.5,0.12), sig = F) #随机换种celltype试试 ks_cpdb_Group_bubble(cpdb_data = data, group_names = c("GO","WT"), analysis_cells = "Macrophages", pathway = c("Adhesion by Laminin","Signaling by Integrin"), cpdb_anno = cpdb_interLR, tag_pos = c(0.4,0.2), sig = F) #只显示显著的，sig=T ks_cpdb_Group_bubble(cpdb_data = data, group_names = c("GO","WT"), analysis_cells = "Endothelial", pathway = c("Signaling by Transforming growth factor","Signaling by Semaphorin"), cpdb_anno = cpdb_interLR, tag_pos = c(0.5,0.12), sig = T)

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测试2：自选受配体，自定义分类！

#测试2 #自选受配体对，注释文件带pathway注释 cpdb_interLR_anno <- read.csv(file = 'cpdb_interLR_anno.csv', header = T, row.names = 1) select_LR <- read.csv('plot_pairs.csv', header = F) ks_cpdb_Group_bubble(cpdb_data = data, group_names = c("GO","WT"), analysis_cells = "Endothelial", select_LR = select_LR$V1, cpdb_anno = cpdb_interLR_anno, tag_pos = c(0.4,0.2), sig = F)

没毛病，非常完美！希望对你有所帮助！