Hi all,
I have a data frame in R with a column of gene identifiers (taken from fasta headers). These vary and include both Ensembl style (e.g. ENSP000000001) and NCBI style (e.g gi|123|ref|XP_000001.1|) as well as others.
I want to extract the accession and version numbers from the NCBI identifiers and create a new column as part of my data frame. Non-NCBI identifiers would have an NA in this column.
For example, I would like to change the following data frame:
df1 <- data.frame(gene = c('ENSP00000123', 'gi|1234567|ref|XP_001234.1|',
'gi|1234567|ref|XP_001267.1|', 'ENSP00000124')
)
To this:
gene accession
1 ENSP00000123 <NA>
2 gi|1234567|ref|XP_001234.1| XP_001234.1
3 gi|1234567|ref|XP_001267.1| XP_001267.1
4 ENSP00000124 <NA>
I have tried using regmatches but this is not working the way I want it to.
df1$accession <- regmatches(df1$gene, regexpr("XP_[0-9]+\\.*[0-9]*", df1$gene))
# results in:
gene accession
1 ENSP00000123 XP_001234.1
2 gi|1234567|ref|XP_001234.1| XP_001267.1
3 gi|1234567|ref|XP_001267.1| XP_001234.1
4 ENSP00000124 XP_001267.1
Any help is greatly appreciated. Thanks in advance.
3 answers
Well, I quickly found a solution using stringr and dplyr here.
library(stringr)
library(dplyr)
df1 <-
df1 %>%
mutate(accession = str_extract(gene, "XP_[0-9]+\\.*[0-9]*"))
gives:
gene accession
1 ENSP00000123 <NA>
2 gi|1234567|ref|XP_001234.1| XP_001234.1
3 gi|1234567|ref|XP_001267.1| XP_001267.1
4 ENSP00000124 <NA>
This is rather a question concerning R language, so you are advised to put it on StackOverflow. Here is my attempt to solve it assuming that the NCBI identifier is always on the same (in this case 4th) position (counting the | as separators):
position_id <- 4
df1$accession <- NA
df1$accession[grep(pattern="XP_", x=df1$gene)] <- limma::strsplit2(x=grep(pattern="XP_", x=df1$gene, value=T), split="\\|")[,position_id]
$ library(stringr)
$ df1 <- data.frame(gene = c('ENSP00000123', 'gi|1234567|ref|XP_001234.1|','gi|1234567|ref|XP_001267.1|', 'ENSP00000124'), stringsAsFactors = F)
$ df1$acession=str_extract(ifelse(grepl("xp", ignore.case = T,df1$gene),df1$gene,NA),"XP_[0-9]+.[0-9]")
output:
> df1
gene acession
1 ENSP00000123 <NA>
2 gi|1234567|ref|XP_001234.1| XP_001234.1
3 gi|1234567|ref|XP_001267.1| XP_001267.1
4 ENSP00000124 <NA>
without NA:
$ library(stringr)
$ df1 <- data.frame(gene = c('ENSP00000123', 'gi|1234567|ref|XP_001234.1|','gi|1234567|ref|XP_001267.1|', 'ENSP00000124'), stringsAsFactors = F)
$ df1$accession=str_split_fixed(df1$gene,'\\|*\\|',5)[,4]
output:
> df1
gene accession
1 ENSP00000123
2 gi|1234567|ref|XP_001234.1| XP_001234.1
3 gi|1234567|ref|XP_001267.1| XP_001267.1
4 ENSP00000124
> library(tidyr)
> df1 <- data.frame(gene = c('ENSP00000123', 'gi|1234567|ref|XP_001234.1|','gi|1234567|ref|XP_001267.1|', 'ENSP00000124'), stringsAsFactors = F)
> df1$accession=separate(df1 , gene, sep = "\\|*\\|",c("","","",""))[,4]
> df1
gene accession
1 ENSP00000123 <NA>
2 gi|1234567|ref|XP_001234.1| XP_001234.1
3 gi|1234567|ref|XP_001267.1| XP_001267.1
4 ENSP00000124 <NA>
> library(tidyr)
> df1 <- data.frame(gene = c('ENSP00000123', 'gi|1234567|ref|XP_001234.1|','gi|1234567|ref|XP_001267.1|', 'ENSP00000124'), stringsAsFactors = F)
> df1$accession=separate(df1 , gene, sep = "\\|*\\|",c("","","",""))[,4]
output:
> df1
gene accession
1 ENSP00000123 <NA>
2 gi|1234567|ref|XP_001234.1| XP_001234.1
3 gi|1234567|ref|XP_001267.1| XP_001267.1
4 ENSP00000124 <NA>
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