Use a separate dataframe to assign groups to another dataframe - r

Question

I am currently working with genetic data where the headers are cell sample names. There are 2 samples from each type of cell collected, and they need to be plotted in a box plot. Due to inconsistent sample naming, I am using a separate .csv file where the user writes the sample name and the group it belongs to. I am trying to use the group_by() function to access the sample data but then use the grouping information from the other .csv file. Is there a way to accomplish what I am trying to do?
Cell Sample Data CSV:
Sample A1 Sample A2 Sample B1 Sample B2
1 3 3 5
Grouping CSV
Samples Group
Sample A 1
Sample B 1
Sample C 2
Sample D 2
My current idea is doing something like this
library(dplyr)
groupFile <- data %>% group_by(groupFile$Group)
however that didn't work, and I am stuck at how to make the data correspond to the grouping file.
Note: I previously uploaded this question without sample data and code and it was closed. I'm hoping this describes the problem well enough.

Answer 1

First let's improve your example cell sample data by including samples that are in different groups:
celldata <- structure(list(`Sample A1` = 1L, `Sample A2` = 3L, `Sample B1` = 3L,
`Sample B2` = 5L, `Sample C1` = 6L, `Sample C2` = 7L),
class = "data.frame", row.names = c(NA, -1L))
And your groups data:
groupdata <- structure(list(Samples = c("Sample A", "Sample B", "Sample C", "Sample D"),
Group = c(1L, 1L, 2L, 2L)), class = "data.frame",
row.names = c(NA, -4L))
Life will be much easier with data in "long" format rather than wide, and with everything in the one dataframe.
We can use tidyr::gather to reshape the cell data, then dplyr::mutate to get Samples without the numeric suffixes and finally, dplyr::left_join to bring samples and groups together:
library(dplyr)
library(tidyr)
celldata %>%
gather(Sample, Value) %>%
mutate(Samples = gsub("\\d+", "", Sample)) %>%
left_join(groupdata)
Result:
Sample Value Samples Group
1 Sample A1 1 Sample A 1
2 Sample A2 3 Sample A 1
3 Sample B1 3 Sample B 1
4 Sample B2 5 Sample B 1
5 Sample C1 6 Sample C 2
6 Sample C2 7 Sample C 2
Now you can group on Group. Depending on what you want to do next, you may want to convert Group to a factor. And if you're using ggplot2, you may not even need to group_by.
For example:
library(ggplot2)
celldata %>%
gather(Sample, Value) %>%
mutate(Samples = gsub("\\d+", "", Sample)) %>%
left_join(groupdata) %>%
mutate(Group = factor(Group)) %>%
ggplot(aes(Group, Value)) +
geom_boxplot() +
geom_jitter(aes(color = Samples)) +
theme_bw()