I have done gene ontology enrichment analysis using Ontologizer. the output is like this :
ID Pop.total Pop.term Study.total Study.term Pop.family Study.family nparents is.trivial p p.adjusted p.min
GO:0000000 15117 15075 3743 3733 0 0 0 true 1.0 1.0 1.0
GO:0008800 15117 3 3743 1 4 1 1 false 0.7500000000000001 0.7500000000000001 0.25000000000000006
GO:0052547 15117 23 3743 6 670 208 3 false 0.7699531541574813 0.7699531541574813 3.789971590544467E-43
GO:0000003 15117 1 3743 1 11028 2874 1 false 0.26060935799429585 0.26060935799429585 9.067827348505459E-5
GO:0052548 15117 22 3743 5 280 100 2 false 0.9446003360272346 0.9446003360272346 3.811732507786439E-33
How can I have translation of GO terms? what does this table means?
You can use simple bash script: I hope this should work
go_convert.sh
#!/bin/bash
GOlist=(`cat $1 | awk '!x[$0]++' | cut -f $3`)
for i in "${GOlist[@]}"
do
cat $2 | grep "$GOlist" >> GO_mapped.txt
done
Run:
./go_convert.sh <YOUR_INPUT_FILE> <GO_DB_FILE_FROM_github> <YOUR_column_number having_GO_IDs>
Sorry use this:
#!/bin/bash
GOlist=(`cat $1 | cut -f $3 | awk '!x[$0]++'`)
for i in "${GOlist[@]}"
do
cat $2 | grep "$i" >> GO_mapped.txt
done
I have ran it on sample files and got the results, check out:
./go_convert.sh input_file.txt sample_go_db.txt 1
http://bioinformatics.kandurilab.org/biostars/files/mapping_ids.zip
You can try this tool which gives the results in more detailed manner. If you are working on Human and Linux system, this tool will be useful for you: Gene Set Clustering based on Functional annotation (GeneSCF)
Or still if you want to translate the IDs which you got, use http://geneontology.org/ and search your GO ID there.
Update: GeneSCF now supports all organisms/species from KEGG and Gene Ontology repository.
I want to translate them, but the question is that, how can I do that in automated manner ? because there are lot's of GO ids for my gene cases (2000) and it's not feasible to copy and paste them in the gene ontology website to search them individually.
You can use this annotation files from GeneSCF to map it, if you are familiar with playing with files: https://github.com/santhilalsubhash/geneSCF/tree/master/annotation
This information is all in the documentation. Click "Help" and then "Help Contents..." Honestly, I'm confused how you got this far without knowing what these fields are, such as the population and study IDs. These would have to be created before the analysis, so you might want to think about whether these results are exactly what you want to test. From the docs:
GO id: The accession number of the GO term
Name: The name of the GO term
NSP: The namespace, or subontology: biological process (B), cellular component (C) or molecular function (F)
P-value: The nominal (uncorrected) P-value resulting from the observed overrepresentation of the GO term
Adj. P-Value: The adjusted P-Value (adjusted by the MTC procedure chosen by the user)
Pop. Count: The number of genes in the population set that are annotated to the GO term in question
Study Count: The number of genes in the study set that are annotated to the GO term in question
If you want to know the definition of your GO term, search it on QuickGO. For example, https://www.ebi.ac.uk/QuickGO/GSearch?q=GO:0008800
it works, but it's create messy file with unnecessary information. what I need is that, the script just add the one line(the line which begin with GO ID) of the GO_mapped.txt file to the last column of my YOUR_INPUT_FILE. Basically first column of my input file is GO ID and I want to add just translation of the GO ID to the last column of my input file. for example for GO:0016021 the last column would be integral component of membrane cellular_component. Can you help me with this?
You can try this new script which merges the output with your input file in the last column (Keep in mind all files should be TAB-separated):
Note: whenever you run this script, please delete the output created from last run... otherwise it will keep on appending into previously created file.
bioinformatics.kandurilab.org/biostars/files/mapping_ids_mergingWithInput.zip
Thanks, but this does not add it to the last column of my input file, for example, one line of my input file is like this:
GO:0000000 15117 15075 3743 3733 0 0 0 true 1.0 1.0 1.0
and what I expect as output is
GO:0000000 15117 15075 3743 3733 0 0 0 true 1.0 1.0 transcription, DNA-templates
Sample Input file:
GO:0002040 dsrg dg
GO:0006351 drfh gjfj
GO:0008283 ksjhgk skjrhgfl
GO:0032466 kjf ksjgf
GO:0032877 öl g
GO:0033301 fnbl ksjg
GO:0045944 hfo jgp
GO:0060707 jpgs jge
Merged annotation to input:
GO:0002040 dsrg dg sprouting angiogenesis
GO:0006351 drfh gjfj transcription, DNA-templated
GO:0008283 ksjhgk skjrhgfl cell proliferation
GO:0032466 kjf ksjgf negative regulation of cytokinesis
GO:0032877 öl g positive regulation of DNA endoreduplication
GO:0033301 fnbl ksjg cell cycle comprising mitosis without cytokinesis
GO:0045944 hfo jgp positive regulation of transcription from RNA polymerase II promoter
GO:0060707 jpgs jge trophoblast giant cell differentiation
In your original post you asked what that table means and I explained it, and also showed how you could get this information from the documentation. Then, you answered and said you know what that information means but your main interest is in the GO definitions. Now, you are asking what the table means again? This is obviously confusing. Please refer to the documentation or my post for a description of the results.
For getting the GO definitions, see the QuickGO WebServices page. There are examples for numerous languages on that page and if you read the documentation you'll see that you can come up with a Bash or Perl script for your task in no time.
Hi Jack, please let me know whether you managed to add terms to your file. I want to know that it worked or not, so that I will decide to keep the script or remove it. Therefore other people in future will know whether to use it or not.
And as SES says please change the post topic from
How to interpret the result of GO analysis using Ontologizer? To How to interpret the result of GO analysis using Ontologizer / mapping GO IDs to GO TERMS.
Because you are asking two different questions in same post.
Santhilal Subhash, I faced with other problem, can you help me with that? How to create your own association file for gene ontology enrichment analysis ?
Log in to answer this question.