网站验证码是如何做的网站做seo教程
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！