Retrieve All Genes Associated With A Go Term

Question: Retrieve All Genes Associated With A Go Term

5.6 years ago by

United Kingdom

enricoferrero • 740 wrote:

Hi,

I'm looking for an easy way to retrieve all the genes in a list that are associated with a certain GO term, preferably using R/Bioconductor packages. I'm not interested in under/overrepresentation or enrichment.

For instance, say I have a list of 1000 genes and I want to create a sublist with only the genes known to be involved in 'heart development'.

Thanks!

R bioconductor go gene-ontology • 13k views

ADD COMMENT • link •

modified 4 months ago by EagleEye • 5.0k • written 5.6 years ago by enricoferrero • 740

5.0 years ago by

Dave Bridges • 1.3k

Ann Arbor, MI

Dave Bridges • 1.3k wrote:

Using biomaRt within R:

library(biomaRt)
ensembl = useMart("ensembl",dataset="hsapiens_gene_ensembl") #uses human ensembl annotations
#gets gene symbol, transcript_id and go_id for all genes annotated with GO:0007507
gene.data <- getBM(attributes=c('hgnc_symbol', 'ensembl_transcript_id', 'go_id'),
                   filters = 'go_id', values = 'GO:0007507', mart = ensembl)

ADD COMMENT • link written 5.0 years ago by Dave Bridges • 1.3k

Hi, I've been trying to use this - and it worked ages ago now I keep getting an error saying

"Error in getBM(attributes = c("wikigene_name", "ensembl_transcript_id",  : 
  Invalid filters(s): go_id"

any suggestions? thanks

ADD REPLY • link written 8 months ago by V • 60

Change "go_id" to "go".

You can find the valid filter names with listFilters(ensembl)

ADD REPLY • link written 8 months ago by agatawesol • 20

5.6 years ago by

Pierre Lindenbaum ♦ 106k

France/Nantes/Institut du Thorax - INSERM UMR1087

Pierre Lindenbaum ♦ 106k wrote:

Not using R: Use quickGO to download all the annotation about your term (and its descendants):

$ curl -s "http://www.ebi.ac.uk/QuickGO/GAnnotation?tax=9606&relType=IP&goid=%20GO:0007507%20&format=tsv" | head | verticalize
>>>    2
$1    DB           UniProtKB
$2    ID           A0PJ49
$3    Splice       -
$4    Symbol       FGFRL1
$5    Taxon        9606
$6    Qualifier    -
$7    GO ID        GO:0003179
$8    GO Name      heart valve morphogenesis
$9    Reference    GO_REF:0000019
$10    Evidence     IEA
$11    With         Ensembl:ENSMUSP00000013633
$12    Aspect       Process
$13    Date         20120825
$14    Source       ENSEMBL
<<<    2

>>>    3
$1    DB           UniProtKB
$2    ID           A0PJ49
$3    Splice       -
$4    Symbol       FGFRL1
$5    Taxon        9606
$6    Qualifier    -
$7    GO ID        GO:0060412
$8    GO Name      ventricular septum morphogenesis
$9    Reference    GO_REF:0000019
$10    Evidence     IEA
$11    With         Ensembl:ENSMUSP00000013633
$12    Aspect       Process
$13    Date         20120825
$14    Source       ENSEMBL
<<<    3

>>>    4
$1    DB           UniProtKB
$2    ID           A0SZU5
$3    Splice       -
$4    Symbol       -
$5    Taxon        9606
$6    Qualifier    -
$7    GO ID        GO:0003007
$8    GO Name      heart morphogenesis
$9    Reference    GO_REF:0000019
$10    Evidence     IEA
$11    With         Ensembl:ENSMUSP00000058354
$12    Aspect       Process
$13    Date         20120825
$14    Source       ENSEMBL
<<<    4

(...)

sort and join with your list of genes.

ADD COMMENT • link written 5.6 years ago by Pierre Lindenbaum ♦ 106k

I love the ease with which you can query data and customize the output with quickGO, but the verticalize in that command really threw me. I thought there was a cool member of the unix tool chain I didn't know, but I googled and found out it's actually a cool program you wrote! What a great way to make sense of data that wraps over numerous lines.

ADD REPLY • link written 5.6 years ago by SES ♦ 8.1k

5.6 years ago by

Malachi Griffith ♦ 16k

Washington University School of Medicine, St. Louis, USA

Malachi Griffith ♦ 16k wrote:

Similarly using Amigo you can craft URLs within a script to pull this info for a list of GO IDs (or query any number of different ways). For example:

http://amigo.geneontology.org/cgi-bin/amigo/term-assoc.cgi?gptype=all&speciesdb=all&taxid=9606&evcode=all&term_assocs=all&term=GO:0007507&action=filter&format=rdfxml

That will return entries for GO:0007507, for human only (taxid=9606), all evidence code types allowed, all term associations allowed. Results are returned in xml format for convenient parsing. You can also download in the GO associations ('go_assoc') format.

ADD COMMENT • link written 5.6 years ago by Malachi Griffith ♦ 16k

5.6 years ago by

enricoferrero • 740

United Kingdom

enricoferrero • 740 wrote:

In the end I just used FlyMine, which is handy because it's where I store my lists of genes anyway. In the list page it's just a matter of selecting the right fiilter (i.e. GO parent term: heart development).

Thanks for your suggestions anyway!

ADD COMMENT • link written 5.6 years ago by enricoferrero • 740

4 months ago by

EagleEye • 5.0k

Sweden

EagleEye • 5.0k wrote:

Try GeneSCF enrichment analysis, it will provide you with all 1000 genes and list all associated GO terms irrespective of their statistical significance.

ADD COMMENT • link modified 4 months ago • written 4 months ago by EagleEye • 5.0k

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