As I said before, there is no such thing as a field not having a value. If there are no characters in a field, the value of that field is an empty string. And, yes, test 2 explicitly fails if the CLINSIG field is an empty string. And since an empty string does not contain | and an empty string is not the same as the string VUS, tests 1, 3, 4, and 5 also fail leaving test 6 to set the Classification field to VUS.
Now that you have a clearer specification for your script, can you write the awk script to perform those tests and produce your desired output? Try to write it and let us see what you come up with. If you get stuck, we'll try to help you fix your problems.
This User Gave Thanks to Don Cragun For This Post:
I will attempt to write an awk that can be used with these requirements. It may be similar to post one in structure, but that is only because I am not yet proficient enough, only the final classified file is needed. Thank you .
---------- Post updated at 12:53 PM ---------- Previous update was at 05:07 AM ----------
Below is my awk for the first 3 conditions as well as the sixth. I know that it needs work but, hopefully I got the basic concepts. Thank you .
You still seem to be having trouble with awk syntax...
Code:
if ($(NF-3 == "|"))
does not look for a pipe symbol somewhere in the 3rd from the last field, it looks for a non-empty, non-zero value in field 0 (which with your sample input is ALWAYS true). This is because the number NF-3 will always be a number and will never be the character |; so the value in parentheses will always be false (i.e. 0) and since $0 is not an empty string and is not a string that just contains (or evaluates to) the value 0, the expression evaluates to true. I used:
Code:
if(index($f["CLINSIG"], "|"))
for this test, but you could also just use:
Code:
if($f["CLINSIG"] ~ /|/)
All of your other if statement expressions have similar problems.
Something more like:
Code:
awk '
BEGIN { # Set input and output field separators:
FS = OFS = "\t"
# Create list of needed field headers:
nfh["Classification"]
nfh["CLINSIG"]
nfh["PopFreqMax"]
nfh["Func.IDP.refGene"]
}
NR == 1 {
# Create array to tranlate needed field headers to field numbers:
for(i = 1; i <= NF; i++)
if($i in nfh)
f[$i] = i
# Verify that all of the needed field headers were found:
for(i in nfh)
if(!(i in f)) {
missing++
printf("Needed field missing: %s\n", i)
}
# If one or more needed fields were not found, give up:
if(missing)
exit 1
}
NR > 1 {# Test #1:
#for(i in nfh) printf("NR=%d: f[\"%s\",%d]=\"%s\"\n",
# NR, i, f[i], $f[i])
if(index($f["CLINSIG"], "|"))
$f["Classification"] = "Conflicting"
else { #Test #2:
if($f["CLINSIG"] != "" && $f["CLINSIG"] != "." &&
$f["CLINSIG"] != "VUS")
$f["Classification"] = $f["CLINSIG"]
else # Tests 3, 4, & 5:
if($f["CLINSIG"] == "VUS" && ( \
($f["Func.IDP.refGene"] == "UTR") || \
($f["PopFreqMax"] > .01) || \
($f["Func.IDP.refGene"] ~ /^spl?icing$/) \
)) $f["Classification"] = "Likely Benign"
else # Test #6:
$f["Classification"] = "VUS"
}
#printf(" out: f[\"%s\",%d]=\"%s\"\n", "Classification",
# f["Classification"], $f["Classification"])
}
1' file > final
with your sample input file (with each sequence of four <space> characters changed to a <tab> character) produces the output:
Code:
R_Index Chr Start End Ref Alt Func.IDP.refGene GeneDetail.IDP.refGene AAChange.IDP.refGene PopFreqMax CLINSIG CLNDBN Classification Quality
1 chr1 40562993 40562993 T C UTR5 NM_000310.3:c.-83A>G . 0.9 . . VUS 15
2 chr5 125887685 125887685 C T splicing NM_001201377.1:exon14:c.1233+28G>A . 0.82 . . VUS 10
3 chr16 2105400 2105400 C T splicing NM_000548.4:exon6:c.482-3C>T . 0.21 not provided|not provided|not provided|not provided|other|Benign TSC Conflicting 25
4 chr16 2110805 2110805 G A exonic . TSC2:NM_000548.4:exon11:c.1110G>A:p.Q370Q .004 Pathogenic TSC Pathogenic 40
If the value of the CLINSIG field contains a | character, set the Classification to Conflicted.
should have been:
If the value of the CLINSIG field contains a | character, set the Classification to Conflicting.
The code above implements this corrected Test 1.
Note that the output for input lines 2 and 3 has the Classification field set to VUS because none of Tests 1 through 5 are met by the data in those lines. Your desired output requested that that field be set to Likely Benign for both of those lines, but I don't see how either of those lines meet your Conditions 2 through 5 (my Tests 3 through 5) which are the tests that would set the Classification field to Likely Benign.
Note also that my code processes the header line to locate the names of the fields that are used in the tests and works using field names instead of trying to decipher what is supposed to be in $(NF - whatever).
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