Hi All

I'm not sure if this is even the correct forum to ask this. I wonder if anyone can offer some advice about where i am going wrong with a loop i'm trying to write for cleaning up UNIPROT data names. 

Basically, the name i have from proteomics analysis is something like tr|A0A02DLI66|A0A02DLI66_MYTGA but i would like to strip it to just A0A02DLI66.

I have gotten to the point where i can manually clean it up per sample using this code: 

 fData(x)$UNPROTKB=fData(x)$DatabaseAccess

  fData(x)$UNPROTKB=gsub(pattern="^[^ab][^ab].", replacement="",x=fData(x)$UNPROTKB)

  fData(x)$UNPROTKB=gsub(pattern="\|..", replacement="",x=fData(x)$UNPROTKB)

but my samples are running quite high and this is time cosuming. So i thought a loop would help and while it is processing, it is not changing anything. I'm unsure if i am missing something in the code which is as follows:

tmp <- sapply(nms, function(.bap) {

  cat("Processing", .bap, "... ")

  x <- get(.bap, envir = .GlobalEnv)

  fData(x)$UNPROTKB=fData(x)$DatabaseAccess

  fData(x)$UNPROTKB=gsub(pattern="^[^ab][^ab].", replacement="",x=fData(x)$UNPROTKB)

  fData(x)$UNPROTKB=gsub(pattern="\|..", replacement="",x=fData(x)$UNPROTKB)

  varnm <- sub("bap", "bap", .bap)

  assign(varnm, x, envir = .GlobalEnv)

  cat("done\n")})

Any help would be much appreciated. 

L

It's not really a Bioconductor question, but maybe tangential enough?

I tend to like the *apply family of functions because I'm old and so are they. So I would normally just do something like

fData(x)$UNIPROTKB <- sapply(strsplit(fData(x)$DatabaseAccess, "\\|"), "[", 2)

Which isn't going to be super fast if you have lots of proteins, but it's one line and relatively straightforward. To decompose, the middle part of that is

strsplit(fData(x)$DatabaseAccess, "\\|")

which generates a list for each value, where we split on the pipe (|) symbol, which has to be escaped with \\ so you split on the literal '|' character. So that does something like

> strstrsplit("tr|A0A02DLI66|A0A02DLI66_MYTGA", "\\|")
[[1]]
[1] "tr"               "A0A02DLI66"       "A0A02DLI66_MYTGA"

and the sapply(<stuff goes here>, "[", 2) part just means 'return the second thing from each list item, and if it can be reduced to a vector, do so, please'. So as a (super boring) example

> lotsastuff <- rep("tr|A0A02DLI66|A0A02DLI66_MYTGA", 30)
> sapply(strsplit(lotsastuff, "\\|"), "[", 2)
 [1] "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66"
 [6] "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66"
[11] "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66"
[16] "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66"
[21] "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66"
[26] "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66" "A0A02DLI66"

This is a typical fasta header (see the following link for a full explanation: https://www.uniprot.org/help/fasta-headers).

While using strsplit is easy to understand it requires a loop (or *apply) to access the AccessionNumber/UnqiueIdentifier. You could use gsub with a different pattern to use a vectorized approach:

fasta <- c(
    "tr|A0A02DLI66|A0A02DLI66_MYTGA",
    "tr|B1XC03|B1XC03_ECODH HU, DNA-binding transcriptional regulator",
    "tr|A9UF05|A9UF05_HUMAN BCR/ABL fusion protein isoform Y3"
)

gsub("^tr\\|([A-Z_0-9-]+)\\|.*$", "\\1", fasta)
# [1] "A0A02DLI66" "B1XC03"     "A9UF05"

(A-Z_0-9-]+) defines a group that contains A-Z, 0-9, - or _ (that are the allowed characters for an AccessionNumber). The pattern matches the whole string but the replacement \\1 is just the predefined group. BTW: You could have a look at Pbase fasta parser if you interested in a full featured parser for fasta headers: https://github.com/ComputationalProteomicsUnit/Pbase/blob/master/R/fasta-functions.R