用R根据logFC和p值批量标注基因上下调的N种方法

           expr      logFC    p.value
gene1 2.4667984 -2.9302068 0.07878848
gene2 1.4482891 -2.9680565 0.04675735
gene3 0.2481085  0.1787332 0.01685758
gene4 0.4244537 -1.0029163 0.02281603
gene5 1.6186835 -1.8350010 0.07323936
gene6 3.3965326 -2.2189805 0.04056557

           expr      logFC    p.value regulation
gene1 2.4667984 -2.9302068 0.07878848    none
gene2 1.4482891 -2.9680565 0.04675735    down
gene3 0.2481085  0.1787332 0.01685758    none
gene4 0.4244537 -1.0029163 0.02281603    down
gene5 1.6186835 -1.8350010 0.07323936    none
gene6 3.3965326 -2.2189805 0.04056557    down

set.seed(1445)
df <- data.frame(expr = runif(100,0.01,5), logFC = runif(100,-3,3), p.value = runif(100,0,0.1))
rownames(df) <- paste0("gene",1:100)
head(df)
test_p <- df$p.value <= 0.05#p.value<0.05
test_up <- df$logFC >=1#上调
test_down <- df$logFC <=-1#下调

library(dplyr)
df <- mutate(df, regulation=test_p+test_up+10*test_down, method1 = "")
table(df$regulation)
#重新赋值
df[df$regulation==2,"method1"] <- "up"
df[df$regulation==11,"method1"] <- "down"
df[df$regulation==0|df$regulation==1|df$regulation==10,"method1"] <- "none"

df$method2 <- ifelse(df$regulation==2, "up",
       ifelse(df$regulation==11, "down", "none"))
head(df)

lookup <- c("2"="up","11"="down","0"="none","1"="none","10"="none")
df$method3 <- lookup[as.character(df$regulation)]
head(df)

df$method4 <- case_when(df$regulation == 2 ~ "up",
                        df$regulation == 11 ~ "down",
                        !df$regulation==2 |!df$regulation==11 ~ "none")

df$method5 <- ifelse(test_p & test_up, "up",
                     ifelse(test_p & test_down, "down","none"))

df$method6 <- case_when(test_p & test_up ~ "up",
          test_p & test_down ~ "down",
          !test_p|!(test_down|test_up) ~ "none")

my_regulation <- function(x){
  if(x==2){
    print("up")
  }else if(x==11){
    print("down")
  }else
    print("none")
}
#循环
method7 <- vector("character", nrow(df))
for (i in 1:nrow(df)) {
  method7[i] <- my_regulation(df$regulation[i])
  i <- i+1
}
#赋值
df$method7 <- data.frame(method7)
head(df)

my_regulation2 <- function(x){
  if(df$p.value[x]<0.05 & df$logFC[x]>1){
    print("up")
  }else if(df$p.value[x]<0.05 & df$logFC[x]< -1){
    print("down")
  }else
    print("none")
}
#循环
method8 <- vector("character",nrow(df))
for (i in 1:nrow(df)) {
  method8[i] <- my_regulation2(i)
  i <- i+1
}
df$method8 <- method8
tail(df)

> head(df)
       expr      logFC    p.value regulation method1 method2 method3 method4 method5 method6 method7 method8
1 2.4667984 -2.9302068 0.07878848         10    none    none    none    none    none    none    none    none
2 1.4482891 -2.9680565 0.04675735         11    down    down    down    down    down    down    down    down
3 0.2481085  0.1787332 0.01685758          1    none    none    none    none    none    none    none    none
4 0.4244537 -1.0029163 0.02281603         11    down    down    down    down    down    down    down    down
5 1.6186835 -1.8350010 0.07323936         10    none    none    none    none    none    none    none    none
6 3.3965326 -2.2189805 0.04056557         11    down    down    down    down    down    down    down    down

for (i in 1:7) {
  mi <- paste0('method',i)
  print(sum(df[,paste0('method',i)]==df[,paste0('method',i+1)]))
  i <- i+1
}

[1] 100
[1] 100
[1] 100
[1] 100
[1] 100
[1] 100
[1] 100