基于另一个数据框/列表对数据框中的列进行子集化 [英] subset a column in data frame based on another data frame/list

问题描述

我有以下 table1 这是一个由 6 列和 8083 行组成的数据框.下面我显示这个 table1 的头部:

I have the following table1 which is a data frame composed of 6 columns and 8083 rows. Below I am displaying the head of this table1:

|gene ID        |   prom_65|   prom_66|  amast_69|  amast_70|   p_value|
|:--------------|---------:|---------:|---------:|---------:|---------:|
|LdBPK_321470.1 |   24.7361|   25.2550|   31.2974|   45.4209| 0.2997430|
|LdBPK_251900.1 |  107.3580|  112.9870|   77.4182|   86.3211| 0.0367792|
|LdBPK_331430.1 |   72.0639|   86.1486|   68.5747|   77.8383| 0.2469355|
|LdBPK_100640.1 |   43.8766|   53.4004|   34.0255|   38.4038| 0.1299948|
|LdBPK_330360.1 | 2382.8700| 1871.9300| 2013.4200| 2482.0600| 0.8466225|
|LdBPK_090870.1 |   49.6488|   53.7134|   59.1175|   66.0931| 0.0843242|

我有另一个数据框，名为 accessions40，它是一个包含 510 个基因 ID 的列表.它是 table1 第一列的子集，即它的所有值 (510) 都包含在 table1 (8083) 的第一列中.accessions40 的头部显示如下:

I have another data frame, called accessions40 which is a list of 510 gene IDs. It is a subset of the first column of table1 i.e. all of its values (510) are contained in the first column of table1 (8083). The head of accessions40 is displayed below:

|V1             |
|:--------------|
|LdBPK_330360.1 |
|LdBPK_283000.1 |
|LdBPK_360210.1 |
|LdBPK_261550.1 |
|LdBPK_367320.1 |
|LdBPK_361420.1 |

我想要做的是:我想生成一个新的 table2，它在第一列(基因 ID)下只包含 accessions40 和table1 中其他五列的相应值.换句话说，我想根据 accessions40 的值对 table1 的第一列进行子集化.

What I want to do is the following: I want to produce a new table2 which contains under the first column (gene ID) only the values present in accessions40 and the corresponding values from the other five columns from table1. In other words, I want to subset the first column of my table1 based on the values of accessions40.

推荐答案

我们可以使用 %in% 得到一个逻辑向量和 subset 'table1 的行'基于此.

We can use %in% to get a logical vector and subset the rows of the 'table1' based on that.

subset(table1, gene_ID %in% accessions40$V1)

<小时>

更好的选择是 data.table

library(data.table)
setDT(table1)[gene_ID %chin% accessions40$V1]

或者使用 dplyr

library(dplyr)
table1 %>%
      filter(gene_ID %in% accessions40$V1)

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