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All identifiers in GO (e.g. referenced in GAF, ontology or associated documents) should be conform to the following format:

 GlobalID = Prefix ':' LocalID
  • Prefixes (aka Database): Each prefix must be registered in the GO xrefs registry metadata yaml file (see below). It should correspond to some known authority. The characters must all be alphanumeric (a-z, A-Z, 0-9), underscores or dashes.
  • The LocalID scheme is under the control of the Database/authority. The characters must all be printable ascii characters, excluding spaces.

We use the term 'identifier' as synonymous with GlobalID, although confusingly some use 'identifier' to refer to what we call LocalID. Our concept of GlobalID corresponds with the W3C standard for CURIEs, see below


Examples of well behaved IDs:

  • GO:0008152
    • Database=GO LocalID=0008152
  • SGD:S000006435
    • Database=SGD LocalID=S000006435
  • ZFIN:ZDB-GENE-980526-166
    • Database=ZFIN LocalID=ZDB-GENE-980526-166
  • FlyBase:FBgn0011293
    • Database=FlyBase LocalID=FBgn0011293

Identifiers in GAFs


In the gene association (GAF) files, the global ID is split across two column: Database goes in column 1, LocalID goes in column 2

For filling in the WITH column, the Global ID should be used. This has to be the case, otherwise it would be difficult to tell where the ID came from

Note that in GPAD and GPI formats, a single column with GlobalID is used

Prefix Registry

The Database should be registered in db-xrefs.yaml, available here:

Our prefix registry is coordinated with and the prefixcommons project:

Identifiers, CURIES and URIs

The GO uses semantic web standards such as OWL and RDF. In these standards, URIs are used to uniquely identify ontology terms, genes and associated provenance entities such as publications.

In order to reconcile URIs with the identifier scheme used in formats such as obo, GAF, and how we display identifiers in publications and portals such as AmiGO, we conceive of GlobalIDs as *Compact URIs* (CURIES).

We assume a constant set of prefixes. For all ontologies used in GO, we assume that these have an OBO library PURL URI, so we have an implicit set of prefix declarations:

  @prefix GO:
  @prefix CL:
  @prefix CHEBI:

Problems with existing usage

The term "identifier" is used in different ways which causes confusion. Our concept of GlobalID corresponds with W3C CURIEs and should be unambiguous.

MGI and prefix doubling

MGI IDs are a major problem

GAF (cols 1-3):

 MGI     MGI:98297       Shh

Using the concatenation rule, this composes to the global ID

  • MGI:MGI:98297

Here we have a doubling up of the MGI prefix.

Note that NCBI previously used 'non-doubled- global identifiers of the form MGI:nnn, but they are now switching to the doubled form MGI:MGI:nnn - see article from Wed, 06 Aug 2014 "Important change coming for HGNC and MGI database identifiers"

Compare with the (well-behaved) ZFIN GAFs and IDs:

 ZFIN    ZDB-GENE-980526-166     shha

(example col1,2,3 in GAF)

col1:col2 =

  • ZFIN:ZDB-GENE-980526-166

This is identical to what NCBI uses in their xref

MGI previously confirmed that the global ID is MGI:MGI:nnnnn, and the local internal ID is MGI:nnnn (but this seems to have changed)


MGI should either

  • change their col2 in their GAFs such that only the number is used (PREFERRED)
  • coordinate with other databases, including NCBI to make it clear that the global ID is MGI:MGI:nnnnn


RGD previously used the same pattern as MGI. As of 2008/06/23 they have confirmed their policy and fixed their files. RGD:nnnn is the global ID. The local ID is purely a number (for both genes and references)

FlyBase vs FB

previously there was confusion as to whether to use FB or FlyBase (or FLYBASE)

in GO in our registry, FB is the canonical prefix, but we include FlyBase as a synonym

Historically, "flybase" was used in but this is now resolved to be "fb" consistent with GO and other resources

NCBI seem to use FLYBASE

See Also

McMurry et al 2017, Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data