制作一个函数来获取数据帧 R

问题描述

我有一个包含数百个样本和数千个变量的数据框。但是这里我给出了一个简单的数据框（my_data）作为说明。我想根据基因所属的簇（基因可以在多个簇中）获取变量相对于基因计数总和的百分比。我知道如何使用数据框操作获取每个百分比。但是，由于我是编码新手，我正在尝试制作一个函数来获取百分比。任何人都可以帮助如何使用我的函数（百分比）获得每个基因的百分比？结果将是“百分比”列上的百分比。非常感谢。

gene = c("CD63","PTN","MT2A","PTGDS","DBI","TIMP1","COX6C","APLP2","GPC1")
gene_count = c(10,15,5,10,25,5)
cluster = c(1,2,3,7,8,9,6,4 )
percent = c(0.1,0.15,0.5,0.1,0.25,0.05,0.05)
my_data = data.frame(gene,gene_count,cluster,percent)
my_data


percent = function(gene,cluster){
for (gene in c(data$gene)){
if (data$gene == gene & data$cluster == cluster)
print(data$gene_count[which(data$gene == gene & data$cluster == cluster)]/sum(data$gene_count))
else print("Gene is not expressed in this cluster")
  }
}

解决方法

您可以通过以下方式编写函数：

percent <- function(data,my_gene,my_cluster) {
  sub_data <- subset(data,gene == my_gene & cluster == my_cluster)
  if(nrow(sub_data)) sum(sub_data$gene_count)/sum(data$gene_count)
  else cat("Gene is not expressed in this cluster")
}

percent(my_data,'PTN',2)
#[1] 0.15

percent(my_data,'ABC',2)
#Gene is not expressed in this cluster

,

这可能有用。

percent_in_total

percent_in_total = function(data,gene_in,cluster_in){
  data %>% 
  filter(gene == gene_in & cluster == cluster_in) %>% 
  .[["gene_count"]]/sum(gene_count)
}
percent_in_total(my_data,"PTN",2)
[1] 0.15

# data.table version
library(data.table)
percent_in_total = function(data,cluster_in){
  setDT(data)[,.SD[gene == gene_in & cluster == cluster_in,gene_count]] / sum(gene_count)
}
percent_in_total(my_data,2)
[1] 0.15

percent_in_cluster

我更喜欢使用 data.table 的语法。为了解释这个过程，对于基因MT2A，.SD[gene == gene_in & cluster == cluster_in,gene_count]是gene_count = 5的数量，sum(.SD[cluster==cluster_in,gene_count])]是cluster = 3的总基因数量，即{{1 }}。

5+5