# RRA结果绘图

## 安装包

- # conda activate rplot
- # conda env remove -n ggVennDiagram
- # conda env remove -n rsf
- conda create -n rsf -c conda-forge r-sf=1.0_4
- conda activate rsf
- library(sf)
- # install.packages(“sf”, version = “1.0-4”)
- install.packages(“ggVennDiagram”)
- conda install -c conda-forge r-ggsci -y
- conda install -c conda-forge r-irkernel -y
- Rscript -e “IRkernel::installspec(name=’ggVennDiagram’, displayname=’r-ggVennDiagram’)”
- conda install -c conda-forge r-venndiagram -y

## 数据准备

    1
    2
    3
    4
    5
    6
    7
    8
    9
    10
    11
    12
    13
    14
    15
    16

    x <- list()
    r <- list()
    r$cell <- readRDS('../A_ref_A_fiig.1_A/DEG.rds')
    r$tissue <- readRDS('../B_ref_A_fiig.1_A/DEG.rds')
    names(r$tissue)[3] <- 'symbol'
    r_up <- lapply(r, FUN = function(x){subset(x, log2FoldChange > 0)})
    x$cell_up <- r_up$cell$symbol
    x$RRA_up <- readRDS('r_up.rds')
    x$RRA_up <- x$RRA_up$Name
    x$tissue_up <- r_up$tissue$symbol
    r_dn <- lapply(r, FUN = function(x){subset(x, log2FoldChange < 0)})
    x$cell_down <- r_dn$cell$symbol
    x$RRA_down <- readRDS('r_dn.rds')
    x$RRA_down <- x$RRA_down$Name
    x$tissue_down <- r_dn$tissue$symbol
    summary(x)

## 绘图1

    1
    2
    3
    4
    5
    6
    7
    8

    #载入所需的R包；
    library(ggplot2)
    library(ggsci)
    library(sf)
    library(ggVennDiagram)
    color4 <- alpha("#99CC00",0.5)
    ggVennDiagram(x[1:6], label_alpha=0) +
      scale_fill_gradient(low='white',high =color4)

## 绘图2

    1
    2
    3
    4
    5
    6
    7
    8
    9
    10
    11
    12
    13
    14
    15
    16
    17
    18
    19
    20
    21
    22

    venn.plot <- venn.diagram(
        x = x[1:3],
        filename = NULL,
        cex = 2.5,
        cat.cex = 2.5,
        cat.dist = c(0.07, 0.07, 0.02),
        cat.pos = c(-20, 20, 20),
        alpha = 0.5,
        fill = c("#99CC00", "#c77cff", '#f8766d')
    );
    grid.draw(venn.plot)
    venn.plot <- venn.diagram(
        x = x[4:6],
        filename = NULL,
        cex = 2.5,
        cat.cex = 2.5,
        cat.dist = c(0.07, 0.07, 0.02),
        cat.pos = c(-20, 20, 20),
        alpha = 0.5,
        fill = c("#99CC00", "#c77cff", '#f8766d')
    );
    grid.draw(venn.plot)

绘图
RRA结果绘图
https://occdn.limour.top/2199.html
Author
Limour
Posted on
August 9, 2022
Licensed under
使用NMF进行聚类 Previous
不同批次但未记录批次时使用DESeq2的方法 Next

#### Search

Keyword