R语言数据处理那些事（三）

缘由

生信之路，道阻且长，记录经验，但渡有缘人。

碎碎念

及时当勉励，岁月不饶人 ——陶渊明

代码

Xu S, Luo C, Chen D, Tang L, Chen L, Liu Z. Whole transcriptome and proteome analyses identify potential targets and mechanisms underlying tumor treating fields against glioblastoma. Cell Death Dis. 2022 Aug 18;13(8):721. doi: 10.1038/s41419-022-05127-7. Erratum in: Cell Death Dis. 2022 Sep 19;13(9):797. doi: 10.1038/s41419-022-05228-3. PMID: 35982032; PMCID: PMC9388668.

1. 如何拆分clusterprofile富集结果的前景集和背景集?

split_ratio <- function(ratio) {
    split_ratio <- strsplit(ratio, "/")
    do.call(rbind, lapply(split_ratio, function(x) data.frame(numerator = as.numeric(x[1]), 
                                                              denominator = as.numeric(x[2])
                                                              )
                          )
            )
}
 

2. 如何基于clusterprofile的结果计算fold enrichment?

meta <- meta %>%
    mutate(
        pathway = str_replace(pathway, "\\D+", "map"),
        metabo_count = as.numeric(metabo_count),
        fgRatio_numerator = split_ratio(fgRatio)$numerator,
        fgRatio_denominator = split_ratio(fgRatio)$denominator,
        bgRatio_numerator = split_ratio(bgRatio)$numerator,
        bgRatio_denominator = split_ratio(bgRatio)$denominator,
        fold_enrichment=(fgRatio_numerator/fgRatio_denominator)/(bgRatio_numerator/bgRatio_denominator)
    )

3. 如何转换将特定样本从字符型为数值型？

df <-df %>% dplyr::select(sample) %>%
    mutate(across(everything(), ~ as.numeric(.))) 

4. 如何在dplyr中将列名设置为变量？？

# 加载必要的库
library(dplyr)
library(stringr)
 
# 创建示例数据框
example_df <- data.frame(
  pathway = c("has00123", "mmu01456", "rno057589")
)
 
process_dataframe <- function(df, pathway_col = "pathway") {
  df %>%
    mutate(
      !!sym(pathway_col) := str_replace_all(.[[pathway_col]], "\\D+", "map")
    )
}
 
processed_df <- process_dataframe(example_df)
 
# 打印处理后的数据框
print("处理后的数据框:")
print(processed_df)

5. 如何dplyr中如何按照行加和？

library(dplyr)  
 df <- tibble(x = c(1, 2, 3), y = c(4, 5, 6))  # 默认情况下，mutate() 不能逐行计算 
 df <- df %>%   rowwise() %>%  # 开启逐行处理模式  
  mutate(sum = sum(c(x, y))) %>%    
  ungroup()  # 恢复为普通数据框