如何使用高级字符串匹配对数据进行子集化 [英] How to subset data with advance string matching

问题描述

我有以下数据框，我想根据匹配的字符串从中提取行.

I have the following data frame from which I would like to extract rows based on matching strings.

> GEMA_EO5
gene_symbol  fold_EO  p_value                           RefSeq_ID      BH_p_value
       KNG1 3.433049 8.56e-28              NM_000893,NM_001102416    1.234245e-24
      REXO4 3.245317 1.78e-27                           NM_020385    2.281367e-24
      VPS29 3.827665 2.22e-25                 NM_057180,NM_016226    2.560770e-22
    CYP51A1 3.363149 5.95e-25              NM_000786,NM_001146152    6.239386e-22
      TNPO2 4.707600 1.60e-23 NM_001136195,NM_001136196,NM_013433    1.538000e-20
      NSDHL 2.703922 6.74e-23              NM_001129765,NM_015922    5.980454e-20
     DPYSL2 5.097382 1.29e-22                           NM_001386    1.062868e-19

所以我想提取例如基于 $RefSeq_ID 中匹配字符串的两行，适用于以下内容:

So I would like to extract e.g. two rows based on matching strings in $RefSeq_ID, that works fine with the following:

> list<-c("NM_001386", "NM_020385")
> GEMA_EO6<-subset(GEMA_EO5, GEMA_EO5$RefSeq_ID %in% list, drop = TRUE)

> GEMA_EO6

gene_symbol  fold_EO  p_value RefSeq_ID    BH_p_value
      REXO4 3.245317 1.78e-27 NM_020385  2.281367e-24
     DPYSL2 5.097382 1.29e-22 NM_001386  1.062868e-19

但有些行有几个用逗号分隔的 RefSeq_ID，所以我正在寻找一种通用方法来判断 $RefSeq_ID 是否包含某个字符串模式，然后对该行进行子集化.

But some of the rows have several RefSeq_IDs separated with commas, so I am looking for a general way of telling if $RefSeq_ID contains a certain string pattern and then subset that row.

推荐答案

要进行部分匹配，您需要使用正则表达式(请参阅 ?grepl).这是您的特定问题的解决方案:

To do partial matching you'll need to use regular expressions (see ?grepl). Here's a solution to your particular problem:

##Notice that the first element appears in 
##a row containing commas
l = c( "NM_013433", "NM_001386", "NM_020385")

要一次测试一个序列，我们只需选择一个特定的 seq id:

To test one sequence at a time, we just select a particular seq id:

R> subset(GEMA_EO5, grepl(l[1], GEMA_EO5$RefSeq_ID))
  gene_symbol fold_EO p_value                           RefSeq_ID BH_p_value
5       TNPO2   4.708 1.6e-23 NM_001136195,NM_001136196,NM_013433  1.538e-20

为了检测多个基因，我们使用 | 操作符:

To test for multiple genes, we use the | operator:

R> paste(l, collapse="|")
[1] "NM_013433|NM_001386|NM_020385"
R> grepl(paste(l, collapse="|"),GEMA_EO5$RefSeq_ID)
[1] FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE

所以

subset(GEMA_EO5, grepl(paste(l, collapse="|"),GEMA_EO5$RefSeq_ID))

应该给你你想要的.

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