split character columns and get names of field in string

I am guessing your data is coming from a VCF file, if so there is a dedicated tool for such problems - bcftools.

Let's create example VCF file for testing:

# subset some data from 1000genomes data
tabix -h ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/release/20100804/ALL.2of4intersection.20100804.genotypes.vcf.gz 17:1471000-1472000 > myFile.vcf
# zip it and index:
bgzip -c myFile.vcf > myFile.vcf.gz
tabix -p vcf myFile.vcf.gz

Now we can use bcftools. Here as an example we are subsetting AF and DP from INFO column:

bcftools query -f '%CHROM %POS %INFO/AF %INFO/DP \n' myFile.vcf.gz 
17  1471199  1916 0.088
17  1471538  2445 0.016
17  1471611  2733 0.239
17  1471623  2815 0.003
17  1471946  1608 0.007
17  1471959  1612 0.014
17  1471975  1610 0.179

See the manual for more query options.

Using regex and the stringi packages:

setDT(myDT) # After creating data.table from structure()

library(stringi)

fields <- unique(unlist(stri_extract_all(regex = "[a-z]+(?==)", myDT$info)))
patterns <- sprintf("(?<=%s=)[^;]+", fields)
myDT[, (fields) := lapply(patterns, function(x) stri_extract(regex = x, info))]
myDT[, !"info"]

    chr  pos type end
1: chr1 <NA>    3   4
2: chr2 <NA> <NA>   6
3: chr4 TRUE    2   5

Edit: To get the correct type it seems (?) type.convert() can be used:

myDT[, (fields) := lapply(patterns, function(x) type.convert(stri_extract(regex = x, info), as.is = TRUE))]

For now, I managed to get what I want with the following code:

newDT <- reshape(splitstackshape::cSplit(myDT, "info", sep=";", "long")[, 
                  c(.SD, tstrsplit(info, "="))], 
                 idvar=c("chr", "pos"), direction="wide", timevar="V4", drop="info")
setnames(newDT, sub("V5\\.", "", names(newDT)))

newDT
#    chr pos type end  pos
#1: chr1 123    3   4 <NA>
#2: chr2 435 <NA>   6 <NA>
#3: chr4 120    2   5 TRUE

Two options to improve the lines above, thanks to @A5C1D2H2I1M1N2O1R2T1 (who gave them in comments) :

. with a double cSplit prior to dcast:

cSplit(cSplit(myDT, "info", ";", "long"), "info", "=")[, dcast(.SD, chr + pos ~ info_1, value.var = "info_2")]

. with cSplit/trstrplit and dcast instead of reshape:

cSplit(myDT, "info", ";", "long")[, c("t1", "t2") := tstrsplit(info, "=", fixed = TRUE)][, dcast(.SD, chr + pos ~ t1, value.var = "t2")]

We could split on ";" then reshape wide-to-long, then split again on "=", then reshape back to long-to-wide:

dcast(
  melt(dt[,  paste0("col", 1:3) := tstrsplit(info, split = ";") ],
       id.vars = c("chr", "pos", "info"))[, -c("info", "variable")][
         ,c("x1", "x2") := tstrsplit(value, split = "=")][
           ,value := NULL][ !is.na(x1), ],
  chr + pos ~ x1, value.var = "x2")

#     chr pos end  pos type
# 1: chr1 123   4 <NA>    3
# 2: chr2 435   6 <NA> <NA>
# 3: chr4 120   5 TRUE    2

---

An improved / more readible version:

dt[, paste0("col", 1:3) := tstrsplit(info, split = ";")
   ][, melt(.SD, id.vars = c("chr", "pos", "info"), na.rm = TRUE)
     ][, -c("info", "variable")
       ][, c("x1", "x2") := tstrsplit(value, split = "=")
         ][, dcast(.SD, chr + pos ~ x1, value.var = "x2")]