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cellphonedb v5受配体多组比较气泡图(原创函数)

cellphonedb v5受配体多组比较气泡图(原创函数)

作者: KS科研分享与服务 | 来源:发表于2024-09-07 09:44 被阅读0次

    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!):https://www.bilibili.com/video/BV1EreueiE7Q/?spm_id_from=333.999.0.0&vd_source=05b5479545ba945a8f5d7b2e7160ea34

    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!


    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))
    

    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)
    
    image.png

    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!

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