2016 Los Angeles GOC Meeting Agenda

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Agenda

Follow-up on outstanding action items from previous GOC meeting in Geneva

Informatics and Infrastructure 5 year plan

Can we have this on this first day? I will give up update on various changes Cjm (talk) 15:11, 5 October 2016 (UTC)

  • replacement of svn
  • metadata-driven infrastructure
  • retiring mySql
  • graphstore
  • new dataflow
  • ...

Annotation Metrics

  • Estimated time: 1 hour
  • What are the best metrics to assess progress in GO annotation?
    • Improved information content - how would that be measured?
    • Number of annotations
    • Number of references
    • Percentage of genome annotated vs percentage of genome with annotatable information?
  • How does LEGO modeling change our assessment of curator contributions?

Protein Complexes

  • Estimated time: 1-2 hours
  • What protein complexes should be in the Cellular Component branch of the ontology?
    • These were the action items from the 2015-09 Washington, D.C. meeting:
      • Action item: new evidence code for capturing complexes, child of IPI (ECO:0000353)
      • Action item: new evidence code for reconstituted biological system consisting of components of more than one species
      • Action item: Form a working group to come up with a process for this migration of responsibilities from GO for protein complex definition. Curators, Darren (PRO), Sandra (IntAct), Paola (GO), David OS, Chris, Peter (Reactome) should be included.

Regulation relations

Regulation and causal relations are central to LEGO annotation and to inference based on LEGO models, but definitions and guidelines still need work to ensure consistency and clarity. DOS: I would like to present progress on the development of the relevant relations along with a proposal for how to improve them. This would probably work best as a collaborative presentation with LEGO annotators (David H & Val?) where we can show application to LEGO models.

Genetic entities in GO annotation

  • What genetic entities do we need to refer to as the primary object of GO annotation and in extended forms of conventional or LEGO annotation?
  • What conventions should we enforce regarding which identifiers to use to refer to these genetic features and how?

Conference Calls

  • Estimated time: 15 minutes
  • Proposal to consolidate LEGO, Annotation, PAINT, and Ontology Development calls into one GO call held weekly on Tuesdays at 8am PST
  • These areas of annotation, and ontology development, are, or have been, converging for some time now and we think it would be a better use of everyone's time to have one weekly call where we discuss any annotation- or ontology-related issues

Annotation Issues - Conventional Annotations

  • Modified protein binding: GO terms & annotations are very inconsistent.
    • Recent github issues:
glycoprotein binding: https://github.com/geneontology/go-ontology/issues/12580#issuecomment-240782020
ubiquitinated protein binding https://github.com/geneontology/go-ontology/issues/12582#issuecomment-240452320

Annotation Issues - LEGO Annotations (Sunday AM?)

  • How are we going to handle ECO codes in Noctua. Currently there are only a limited number of codes that fall under 'used in manual assertion'. If we use codes that are not specific to the manual assertion part of the ontology, then they map to EXP. Are we going to request the entire set of codes that we think we might want to use or are we going to have an automated way to map to the correct code?
  • Are we going to allow Noctua to make annotations to the root nodes of the ontology?
    • This would be useful for contextual annotations that are to otherwise root nodes.
    • However some groups block these kinds of annotations because in the past, these annotations were used to keep track of genes about which we had no information.
    • Note that the evidence code for a root node annotation in Noctua would/could be different in that the curator might assert that a gene product has some molecular function due to the observation that, when mutated, there is a phenotypic outcome, e.g. apoptosis execution fails.
    • This is a different statement from no biological data (ND) in which there is no information at all to assert a role in any biological process.
  • MGI's experience roundtripping with Noctua Models (DPH)

Production

New data flow (Chris)