使用正则表达式在数据框中查找行

时间:2022-06-01 20:08:10

I have a translation table (trans_df):

我有一个翻译表(trans_df):

trans_df <- read.table(text = "rs1065852 rs201377835 rs28371706 rs5030655 rs5030865 rs3892097 rs35742686 rs5030656 rs5030867 rs28371725 rs59421388
                       G           C          G         A         C         C          T        CTT         T          C          C
                       G           C          G         A         C         C        del        CTT         T          C          C
                       A           C          G         A         C         T          T        CTT         T          C          C
                     del         del        del       del       del       del        del        del       del        del        del
                       G           C          G       del         C         C          T        CTT         T          C          C
                       G           C          G         A         C         C          T        CTT         G          C          C
                       G           C          G         A         C         C          T        del         T          C          C
                       A           C          G         A         C         C          T        CTT         T          C          C
                       G           C          A         A         C         C          T        CTT         T          C          C
                       G           C          G         A         C         C          T        CTT         T          C          T
                       G           C          G         A         C         C          T        CTT         T          T          C",header=TRUE, stringsAsFactors = FALSE, colClasses = "character")

and input :

并输入:

    input <- read.table(text = "rs1065852 rs201377835 rs28371706 rs5030655 rs5030865 rs3892097 rs35742686 rs5030656 rs5030867 rs28371725 rs59421388
+ G|A           C        G|A         A         C       T|C          T  CTT         T        C|T          C", header = TRUE, stringsAsFactors = FALSE, colClasses = "character")

I want to find the input row in the trans_df using regular expression. I have achieved it by position:

我想使用正则表达式在trans_df中找到输入行。我按位置实现了它:

Reduce(intersect,lapply(seq(1, ncol(trans_df)), 
                          function(i) {grep(pattern = input[, i], 
                          trans_df[, i])}))

Is there any way to do this where pattern = input? Please advise.

有没有办法在pattern = input中执行此操作?请指教。

2 个解决方案

#1


1  

You can use Mapto achieve that, i.e.

您可以使用Mapto实现该目标,即

Map(grep, input, trans_df)

However, that makes the assumption that your columns match one-on-one. If that does not stand, then you can use match to make them the same, i.e.

但是,这会假设您的列与一对一匹配。如果这不成立,那么你可以使用匹配使它们相同,即

Map(grep, input[match(names(input), names(trans_df))], trans_df)
#or in the same sense and to keep input intact,
Map(grep, input, trans_df[match(names(trans_df), names(input))])

However, I think that would beat your purpose though.

但是,我认为这会打败你的目的。

#2


1  

I would just use subset() here and pass it the criteria for a matching row. In this case, the criteria involves checking each column in the data frame against a set of known values. Assuming that input is a named vector, we can try the following code:

我只想在这里使用subset()并传递匹配行的条件。在这种情况下,标准涉及根据一组已知值检查数据框中的每一列。假设输入是命名向量,我们可以尝试以下代码:

subset(trans_df, rs1065852 == input["rs1065852"] & rs201377835 == input["rs201377835"] &
       ... & rs59421388 == input["rs59421388"])

#1


1  

You can use Mapto achieve that, i.e.

您可以使用Mapto实现该目标,即

Map(grep, input, trans_df)

However, that makes the assumption that your columns match one-on-one. If that does not stand, then you can use match to make them the same, i.e.

但是,这会假设您的列与一对一匹配。如果这不成立,那么你可以使用匹配使它们相同,即

Map(grep, input[match(names(input), names(trans_df))], trans_df)
#or in the same sense and to keep input intact,
Map(grep, input, trans_df[match(names(trans_df), names(input))])

However, I think that would beat your purpose though.

但是,我认为这会打败你的目的。

#2


1  

I would just use subset() here and pass it the criteria for a matching row. In this case, the criteria involves checking each column in the data frame against a set of known values. Assuming that input is a named vector, we can try the following code:

我只想在这里使用subset()并传递匹配行的条件。在这种情况下,标准涉及根据一组已知值检查数据框中的每一列。假设输入是命名向量,我们可以尝试以下代码:

subset(trans_df, rs1065852 == input["rs1065852"] & rs201377835 == input["rs201377835"] &
       ... & rs59421388 == input["rs59421388"])