在 df2 中识别 df1 中的元素，然后在 df2 中使用 R 重合的那些行中添加列

Question

I have a dataframe with two columns (genome) and a dataframe with one column (list_SSNP).

What I am trying to do is to add a third and fourth columns in my Genome dataframe and add the value "1" for those positions in Genome that appear in list_SSNP and, separately, in list_SCPG.

I am trying to get an output dataframe that looks like this:

Gene_Symbol       CHR        SNP     
A1BG             19q13.43             
PDE1C            12p13.31     1        

This is part of the content of Genome and I have included a reproducible example:

Genome <- c()
Genome$Gene_Symbol <- c("A1BG", "A1BG-AS1", "A1CF", "A2M", "PDE1C")     
Genome$CHR <- c("19q13.43", "19q13.43", "10q11.23", "12p13.31", "12p13.31")
Gene_Symbol CHR
        1   A1BG        19q13.43
        2   A1BG-AS1    19q13.43
        3   A1CF        10q11.23
        4   A2M         12p13.31
        5   PDE1C       12p13.31

And this is part of the content of list_SSNP:

list_SSNP <- c("PDE1C", "IMMP2L", "ZCCHC14", "NOS1AP", "HARBI1")
    Gene_Symbol
1   PDE1C
2   IMMP2L
3   ZCCHC14
4   NOS1AP
5   HARBI1

Using only 1 of the dataframes (list_SSNP), which is what I am attempting to do first, what I have tried to do is a loop through the genome dataframe and for element i (row) in my Genome if the element i of my list_SSNP dataframe is like element i in my Genome dataframe, then add the number 1 to a third column, but when I execute this code, nothing happens.

Full_genome <- read.table("FULL_GENOME.txt", header=TRUE, sep = "\t", dec = ',', na.strings=c("","NA"), fill=TRUE)
Genome <- Full_genome[,c(2,3)]
names(Genome) <- c("Gene_Symbol", "CHR")

list_SSNP <- as.data.frame(Gene_SSNP$Gene_Symbol)

for (i in 1: dim (Genome) [1]) {
  if(list_SSNP[i] %in% Genome[i,1]){
    Genome[i,3] <- 1 
  }
}

Just to further clarify, I have checked that all the elements from list_SSNP appear in Genome, so it is absolutely certain that it is not a matter of not finding any coincidences.

EDIT:

I have come to realize that my example does not specify that the entries in list_SSNP and Genome are unique and have no duplicates and that Genome has about 30k lines of entries, while list_SSNP has 49. I just want to add a column in Genome and a number 1 in those rows where the entry exists in both Genome and list_SSNP.

Answer 1

I believe this could help. You can try this code:

#Data
Genome <- data.frame(Gene_Symbol = c("A1BG", "A1BG-AS1", "A1CF", "A2M", "PDE1C"),
                     CHR = c("19q13.43", "19q13.43", "10q11.23", "12p13.31", "12p13.31"),
                     stringsAsFactors = F)
list_SSNP <- c("PDE1C", "IMMP2L", "ZCCHC14", "NOS1AP", "HARBI1")
#Collapse
vecc <- paste0(list_SSNP,collapse = '|')
#Contrast
Genome$SNP <- as.numeric(grepl(pattern = vecc,x = Genome$Gene_Symbol))

Output:

  Gene_Symbol      CHR SNP
1        A1BG 19q13.43   0
2    A1BG-AS1 19q13.43   0
3        A1CF 10q11.23   0
4         A2M 12p13.31   0
5       PDE1C 12p13.31   1

Answer 2

I may miss something important here, but the problem is formulated quite specifically to its domain. So, when I abtsracted it, I may have overseen an issue with my proposed solultion.

However, I understand that list_SSNP can have a SNP entry multiple times. So first of all, you could create a list of unique SNPs with the count of its occurences

library(dplyr)

list_SSNP = data.frame(SNP = c("PDE1C", "IMMP2L", "ZCCHC14", "NOS1AP", "HARBI1"))
unique_SSNP = list_SSNP %>% 
    group_by(SNP) %>% 
    # the summarize() could be replaced by count I guess, but I usually use this for more control
    summarize(count = n()) 

And now you use a left_join

Genome = data.frame(Gene_Symbol = c("A1BG", "A1BG-AS1", "A1CF", "A2M", "PDE1C"),
                     CHR = c("19q13.43", "19q13.43", "10q11.23", "12p13.31", "12p13.31"),
                     stringsAsFactors = F)

Genome_extended = Genome %>% 
    left_join(unique_SSNP, by = c("Gene_Symbol" = "SNP"))

The count column in the extended dataframe would be NAs for non-existing SNPs and you could fill the NAs with a variety of commands from dplyr, tidyr or even base R.