Command Or Script To Generate An Annotation File For Blast2Go

Question: Command Or Script To Generate An Annotation File For Blast2Go

6.8 years ago by

lzsph • 70

lzsph • 70 wrote:

Dear all,

We have got RNA-Seq of a plant without a reference genome, so we de novo assembled its transcriptome using Trinity. Now we have an annotation file of this transcriptome. I want to generate GO (Gene Ontology) functional classification using Blast2GO. But re-mapping my Blast XML results in Blast2GO is time consuming (I tried that of my ~200,000 transcripts in my transcriptome).

An alternative way to generate GO function classification is importing the annotation file (with a suffix .annot according to Blast2GO manual), the .annot file looks like below (You can also get this example .annot file at http://www.blast2go.com/b2glaunch/resources , named b2g_example_files.zip): p.s. If you can't see this picture from Flickr, I also put it on GitHub

enter image description here

But our annotation file was not generated by Blast2GO, it's a CSV file like this below (a little mess):

X01_query_id, X06_hit_title, X07_molecular_function, X08_biological_process, X09_cellular_component ##header of the CSV file

comp1000113_c0_seq1, Cc-nbs resistance protein [Medicago truncatula], GO:0043531 // ADP binding;GO:0005524 // ATP binding;GO:0017111 // nucleoside-triphosphatase activity, GO:0006952 // defense response,

comp10001_c0_seq1, Pistil-specific extensin-like protein [Medicago truncatula], , ,

comp1000255_c0_seq1, F-box protein [Medicago truncatula], , ,

comp1000736_c0_seq1, Alpha-L-arabinofuranosidase [Medicago truncatula],GO:0046556 // alpha-N-arabinofuranosidase activity, GO:0046373 // L-arabinose metabolic process,

comp1000860_c0_seq1, Protein kinase [Medicago truncatula], GO:0005524 // ATP binding;GO:0004674 // protein serine/threonine kinase activity, ,

I need to bother you to help me provide some command or some scripts to generated a .annot file like this below:

ignore those lines without GO IDs

p.s. If you can't see this picture from Flickr, I also put it on GitHub

enter image description here

I look forward to hearing from all of you soon.

Thank you and best regards,

lzsph

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modified 6.8 years ago by Whetting • 1.5k • written 6.8 years ago by lzsph • 70

import re out=open("test.annot","a") with open("input.csv","rU") as f: for line in f: line=line.rstrip() if "GO" in line: x=1 line=line.split(",") for m in re.findall("GO:\d{7}",str(line[2:])): if x==1: print >>out, line[0], m, line[1].rsplit(" [")[0] x=x+1 else: print >>out, line[0], m out.close()

comp1000113c0seq1 GO:0043531 Cc-nbs resistance protein comp1000113c0seq1 GO:0005524 comp1000113c0seq1 GO:0017111 comp1000113c0seq1 GO:0006952 comp1000736c0seq1 GO:0046556 Alpha-L-arabinofuranosidase comp1000736c0seq1 GO:0046373 comp1000860c0seq1 GO:0005524 Protein kinase comp1000860c0seq1 GO:0004674

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