问题
right now I'm refactoring an 'base'-based R script by using 'dplyr' instead.
Basically, I want to group_by Gene and subtract the values group-wise by a group that matches a given condition. In this case, I want values of Gene == 'C' and subtract them from all others.
Simplified data:
x <- data.frame('gene' = c('A','A','A','B','B','B','C','C','C'),
'sample' = rep_len(c('wt','mut1','mut2'),3),
'value' = c(32.3,31,30.5,25,25.3,22.1,20.5,21.2,19.8))
gene sample value
1 A wt 32.3
2 A mut1 31.0
3 A mut2 30.5
4 B wt 25.0
5 B mut1 25.3
6 B mut2 22.1
7 C wt 20.5
8 C mut1 21.2
9 C mut2 19.8
Desired output:
gene sample value deltaC
1 A wt 32.3 11.8
2 A mut1 31.0 9.8
3 A mut2 30.5 10.7
4 B wt 25.0 4.5
5 B mut1 25.3 4.1
6 B mut2 22.1 2.3
7 C wt 20.5 0.0
8 C mut1 21.2 0.0
9 C mut2 19.8 0.0
I base, it's not a big deal, but I'm wondering whether there is a simple solution using dplyr.
'Pseudo'code:
df %>%
group_by(Gene) %>%
mutate(deltaC = Value - Value(where Gene == 'C'))
Is there any kind of function that allows me to access only those values of Gene == 'C'? Of course I could also do a subset before, but I would like to do it in one step :)
回答1:
If you wanted to avoid the $ completely, you could use dplyr::pull like so:
df %>%
group_by(gene) %>%
mutate(deltaC = value - filter(., gene == 'C') %>% pull(value))
dplyr::pull is basically just the pipe friendly, dplyr equivalent to df$value or df$[["value"]]
Also, using the . inside of the filter statement represents the data that is being piped into the mutate statement.
回答2:
You basically had it! You can subset the data frame based on any condition within your mutate call:
df <- data.frame('gene' = c('A','A','A','B','B','B','C','C','C'),
'sample' = rep_len(c('wt','mut1','mut2'),3),
'value' = c(32.3,31,30.5,25,25.3,22.1,20.5,21.2,19.8))
Nicholas Hassan pointed out a problem with the original version of this answer. While you can group by "gene" and then mutate using a filtered version of the original data.frame, what you most likely want to do is to group by "sample" and then subset within the sample group on "gene":
df %>%
group_by(sample) %>%
mutate(deltaC = value - value[gene == 'C'])
# A tibble: 9 x 4
# Groups: sample [3]
gene sample value deltaC
<fct> <fct> <dbl> <dbl>
1 A wt 32.3 11.8
2 A mut1 31 9.8
3 A mut2 30.5 10.7
4 B wt 25 4.5
5 B mut1 25.3 4.1
6 B mut2 22.1 2.3
7 C wt 20.5 0
8 C mut1 21.2 0
9 C mut2 19.8 0
Within the grouped data.frame, mutate acts on each group as its own mini-data frame, so you can subset the value vector to just the row where gene == 'C' and subtract that from the entire value variable in that group to make deltaC.
来源：https://stackoverflow.com/questions/49536016/dplyr-subtracting-values-group-wise-by-group-that-matches-given-condition