前面我們發(fā)布了關(guān)于cellchat的函數(shù)(連夜更新---別說兩組了，這個cellchat多組比較氣泡圖函數(shù)10組也能做了)。因為cellchat比較好入手破加，所以先開刀纱意。很多小伙伴說有沒有cpdb的狡刘，其實在寫函數(shù)之初，我們就考慮到了飒箭，只不過先從cellchat好入手安皱，本來以為套用可能大差不差调鬓，結(jié)果cpdb在數(shù)據(jù)上有很大出入，所以這次費了點時間酌伊。However，最終效果剛剛的缀踪！

參考：函數(shù)B站解說視頻（一定要看使用方法哦＞幼）：https://www.bilibili.com/video/BV1EreueiE7Q/?spm_id_from=333.999.0.0&vd_source=05b5479545ba945a8f5d7b2e7160ea34

函數(shù)主體：也是支持多組，支持自選受配體驴娃，自選pathway奏候，自定義分類！

image.png

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))

測試1：選定通路

#測試1：cpdb_anno沒有pathway唇敞，用cpdb默認的蔗草，用通路選擇
cpdb_interLR <- read.csv(file="cpdb_interLR",header = T)
#選定pathway，注釋文件中沒有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)


#隨機換種celltype試試
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)

#只顯示顯著的疆柔，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)

image.png

測試2：自選受配體咒精，自定義分類！

#測試2
#自選受配體對旷档，注釋文件帶pathway注釋
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)

沒毛病模叙，非常完美！希望對你有所幫助鞋屈！