Difference between revisions of "GO 18th Consortium Meeting Minutes Day 1"
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== AmiGO – Amelia ==
== AmiGO – Amelia ==
AmiGO enhancements new search features demo
Term enrichment . .
Revision as of 09:57, 15 October 2007
Sunday morning, September 23, 2007 (Day 2 Minutes)
- 1 Introductions chronologically:
- 2 Progress Reports
- 3 Ontology Development 1 - Midori Harris
- 4 Ontology Development 2 - David Hill
- 5 Ontology Development 3 - Chris Mungall
- 6 Target Gene Identification (Priority genes)
- 7 Ortholog Identification
- 8 Metrics
- 9 Annotation Outreach – Jen Deegan
- 10 User Advocacy - Eurie
- 11 Production Systems - Ben Hitz
- 12 AmiGO – Amelia
- 13 Action Items Review
- 14 Reactome - Peter D’Eustachio
- 15 ‘Taxon and GO’ - Jen Deegan
- 16 Summary of action Items from Day 1
2007 Dmitry Sitnikov MGI, Seth Carbon BBOP
2006 Jim Hu E. coli, Susan Tweedie FlyBase, Trudi Torto-Alalibo PAMGO, Donghui Li TAIR
2005 Ben Hitz SGD
2004 Doug Howe ZFIN, Ruth Lovering UCL, Victoria Petri RGD
2003 Jen Deegan GO, Emily Dimmer GOA, Alex Diehl MGI, Mary Dolan MGI, Karen Eilbeck SO, Petra Fey dDB, Ranjana Kishore Caltech, Pascale Gaudet dDB, Kimberley Van Auken Caltech
2002 John Day-Richter BBOP, Eurie Hong SGD, Tanya Berardini TAIR, Amelia Ireland GO
2001 Rama Balakrishnan SGD, Michelle Gwinn Giglio TIGR, Harold Drabkin MGI
2000 Rolf Apweiler EBI, Val Wood Sanger, Rex Chisholm dDB, Chris Mungall BBOP
1999 Midori Harris GO, Kara Dolinski PU, David Hill MGI
1998 Suzi Lewis BBOP, Michael Ashburner, Mike Cherry SGD, Judith Blake MGI
Next year the GO Consortium effort will celebrate its 10th birthday.
2007 Progress Report for NHGRI due Jan. 1, 2008
These reports will review accomplishments to date. We are using the itemized list of sub-aims from the grant to organize these
Aim 1: We will maintain comprehensive, logically rigorous and biologically accurate ontologies.
Ontology Development 1 - Midori Harris
All content meeting related changes documented on Ontology Development Wiki
is_a complete was almost finished last meeting, but is now done and a system is in place to make sure it remains so.
- Three high level terms need to be disjoint – cellular process, multicellular organism process and multi-organism process. General notes on is_a complete: Isa-complete_BP
Topics also overviewed; priority list on main Ontology Development wiki page.
Content meetings have been held for:
- Transporter activities extensive work via web conferences
- Medium-scale content changes:
- synaptic plasticity
- RNA processing
Michael Ashburner: Question IMG-to-GO and FIGS-to-GO mappings.
- Jen, Midori: the IMG to GO mapping is mostly finished. These items are waiting for Jane to return.
Chris M: mappings between the BP and MF terms still need to be done.
JB/SL: wiki is a valuable resource, however it can get muddled sometimes – managers should keep track.
Alex: if you add new large section you should send out a general email.
ACTION ITEM – tutorial on wiki discipline (assigned to Jim Hu).
Rex – in addition, there could be a group of wiki experts formed, who people could contact for advice.
Ontology Development 2 - David Hill
1) Taxon and sensu.
“Sensu” confused users and curators, and editors became lazy in its implementation and accurate definitions were not created. Sensu terms have been renamed, merged or obsoleted (how many?) in collaboration with domain experts.
- Note added after meeting: We would have to run obodiff to get counts for renamed vs. merged vs. obsolete, but we started in April with 229 'sensu' terms, and there are now 80 remaining in the live file. Of these, several are sorted out in the 'fruiting_body.obo' file in go/scratch/, and the remainder (about 60) are listed on the last sensu meeting notes page.
Definitions now need to state how a process occurs differently in the different organisms. If it is impossible to state this, then child terms will not be created. In future, term requests need to include reasons how a process occurs differently in different organisms.
Synonyms containing the sensu information are kept for these terms.
The general consensus at the meeting seemed to be that rather than create long convoluted term names, we would still be allowed to create a term such as plant-type vasculature as long as the definition clearly differentiated the terms.
Chris M: these mappings are complex
Waiting for OBO-Edit 2.0 for help on cross-products.
GO will soon add a new relationship, 'regulates'. Regulation-of-process terms will then be changed from part_of the process to regulates (for example, 'regulation of metabolism part_of metabolism' will become 'regulation of metabolism regulates metabolism').
During the is_a-complete work, three top-level regulation terms were added to represent three categories of biological regulation: regulation of molecular function, regulation of biological process, regulation of biological quality.
Chris has generated a report (go/scratch/regulation-of-non-process.txt) of all descendants of 'regulation of biological process' where there is no term for the process being regulated. David Hill is going through the report (not as bad a task as he'd feared), and has found that the violations fall into three categories, corresponding to the three parts of the Regulation Worksheet:
- Part 1: The regulation term describes regulation of a molecular function or a biological quality, so the term is o.k.
- Part 2: The regulation term is a legitimate subtype of its parent, but a more specific process term isn't required. Example:
- GO has 'regulation of transcription involved in forebrain patterning' and 'regulation of transcription', but not 'transcription involved in forebrain patterning'. 'Regulation of transcription involved in forebrain patterning' is
- Part_of forebrain patterning (check)
- Is_a regulation of transcription (check)
- 'Transcription of forebrain patterning' is not necessary -- it is essentially the same process as transcription
This term will inherit the regulates relationship through its is_a paretn and will regulate 'transcription'. It will remain a part_of forebrain patterning since every instance of this process is a part_of an instance of forebrain patterning.
- Part 1: Actual problems of various kinds; David has made suggestions about how to handle them, which everyone should check -- especially the ones with question marks.
Chris Mungall: there are problems with cross-products, and would be easier if the parent terms did exist.
David H: this will be resolved once the parent terms do exist.
David H: concern about consistency in regulates relationships. In some cases, negative and positive regulation of a process are part_of the parent and in some cases they are is_a of the parent. We need to be consistent about this. For now, negative and positive regulation of a biological quality are a special case. When you are regulating a biological quality, the regulation is a balance of the positive and negative processes. Therefore, the positive and negative children are part_of the regulation of the quality. Suggestion to use homeostasis terms for overall regulation of biological quality [midori]
CM: will look at relationships between cell types and GO terms: use as a guide to populate GO with missing terms.
Q. VW: How existing annotations are affected by relationships change Eg transcription intiation. may have annotated more granularly to regulation of transcription initiation when there is direct involvement. Topic for annotation discussion at some point?
A (David, Midori): The 'regulates' relationship shouldn't affect annotations. Basically the part_of relationships already exist and we will simply replace it with regulates. We are already annotating to regulates terms and it shouldn't change. What will be different is how we process annotations. We will be able to decide whether or not we should include regulates children.
ACTION ITEM (ALL) Look at and comment on outstanding items (search on ?)
ACTION ITEM Check whether there should be a relationship between pigment metabolic process and pigmentation
3) Information content analysis. Collaboration with MIT/Harvard group.
MIT and Harvard got in contact with GO, were interested in measuring information content of a GO term. They looked at the number of annotations to a term related to its position in the ontology.
They developed a statistical algorithm to determine information content based on the assumption that if not many genes are annotated to a term it has a high information content and a term with lots of gene products annotated has a low information content
David, Midori and Jane then looked for outliers with respect to information content (finding terms that were either too specific, at a higher or lower level than they should be)
Took higher level terms which had too few annotations compared to other things the same distance from the root and looked if they could be relocated. e.g pilus retraction was a direct child of 'cell physiological process' and was relocated to pilus organisation and biogenesis, so that it was at an appropriate level in the GO hierarchy.
Similarly lots of specific terms had a larger than expected number of annotation eg. Olfactory receptor activity
Some of the annotation distributions between terms also just reflected biological differences e.g. cation and anion transport terms: there are more cation transporter genes than anion transporters, the two terms are at the same level in the ontology - as they should be. Therefore this analysis can only draw attention to particular parts of the ontology which a curator then can examine.
Q: JDR Is it possible to put this analysis into GOC tools?
A: CM – the analysis is already in database, can be used.
AD: this is something which can be repeated semi-regularly, but not to dwell on too much.
DH: this has beeen a very good collaboration experience, and had produced good contacts to continue relationships with. SR: We know of other groups that could also get in touch which are interested in this area as well - will get in touch with David Hill. JB: annotations give power to these kinds of approaches. And until we have an annotation core we are restricting this kind of potential activity.
Ontology Development 3 - Chris Mungall
Wiki for ontology structure (should be merged with Ontology Development)
1. Mining Reactome links to link process to function – more after lunch.
2. Internal cross products can start to be created and maintained in the ontology. OBO-Edit 2.0 will make it easier to maintain these cross products.
New cross product guide on wiki. Links to ongoing work on BP – CP cross products;
e.g. could link histone deacetylase complex to histone deacetylase activity (this type of linking is easier than creating BF to MF links)
Internal links (existing)
External links (function to process links)
External links (x products)
Links need to be treated with caution. Links are kept in a file separate to GO at the moment, as people could make erroneous propagation of annotaitons between the Gene Ontologies (i.e. just because someone annotates to a certain process, it does not mean they should necessarily annotate to the linked function).
- people are using this qualifier incorrectly in annoations. VW: take Histone Deacetylase complex as an example, this is a very large complex with many molecular functions. Therefore one complex can be linked to many different functions. We should use contributes_to *only* in those instances where the annotator does not know which subunit provides a function. JB: no, contributes_to can be used also when you *do* know the individual contributions of subunits. MD: often subunits which do not have a specific activity themselves are involved in enabling another subunit providing the activity. VW: but this does not hold ofr all complexes, we are using this qualifier in too many different ways. DH: often, if a subunit is knocked-out, the observer cannot tell if the subunit has a direct or indirect influence on the resulting phenotype. Therefore in addition often the 'contributes_to' qualifier is missing.
- discussion postponed
Internal cross-products If cross-products were maintained in the GO directly, it would make life easier. Cross-products will be more manageable in OBO-Edit 2.0 where there are many features - can use a 'Cross-Product Matrix Editor' - can see the possible cross-product/GO combinations, parents and children of a term. - this helps identify missing links in the DAG. - in addition, there will be an ontology repair option, which can introduce these links, e.g. missing is_a links. DH: we want to use this to go through the logic of the regulates relationship - as concern about ensuring consistency. CM: will also look at relationships bettween cell types and GO terms: and can use as a guide to populate GO with such missing terms. ... more on cross-product logistics later.
Karen Eilbeck SO Progress
Development : March–>August joined J Thornton group - Gabi Reeves for BioSapiens project on protein terms, 96 new terms for polypeptides have now been added to SO.
Mark Hathon (with Barry Smith)BioSmith, Buffalo – ongoing work on regulatory regions.
Content meeting in June, HLA immunology community – looking for terms to describe variants. Added new terms, rearranging of SO – very productive. Assigned work to Alex, nothing to report.
Collaboration with Arian at phyGo. Mobile genetic elements for viruses. This is in parallel with work happening in GO.
Working on synonyms with Colin Batchelor, and over 400 new synonyms have been added to SO.
Release SO now every 2 months. Therefore there is a stable and leading-edge version for those interested.
Changing requirements for GFF3 - this not done yet.
Karen dropping down to 60% on this project.
Aim2: We will comprehensively annotate reference genomes in as complete detail as possible.
Reference Genome Annotation Project - Rex Chisholm
Aim3: We will support annotation across all organisms.
Purpose: to provide comprehensive, robust collection of annotations for 12 genomes. These genomes have the most published data, have a genome database and experienced GO annotators. These high-quality annotations will be a resource for other groups to transfer to genes in their species.
Complete/comprehensive annotation includes measures of breadth and depth.
Breadth – every gene annotated.
Depth – gene annotated to the highest possible knowledge. If there are only a small amount of papers (5-10) then the curator should read all. If extensive then the curator should be selective, completion best assessed by a curator)
Target Gene Identification (Priority genes)
250 genes have now been targeted for curation. The target method has now been changed, targets are now (as of last month) selected based on disease type. Gene when mutated should contribute centrally to a disease phenotype(OMIM). This method has been generally successful, however there is now a challenge for mammalian groups with the increased literature load. Also a challenge for non-mammals - orthologs may not always be available (e.g. neurological genes in yeast). These challenges need to be balanced.
Need to have a good set of orthologs.
Need to find ways of facilitating this work through tools, no obvious choice as yet. e.g. InParanoid have problems in keeping pace and providing up-to-date sets. Would be good to have a ortholog set automatically provided which curators could then validate.
Currently use Google spreadsheets for target lists and information on curation progress. However this is not robust enough and time consuming. A database will be developed to handle this data and requirements have been written up. This will mean that the Ref Genome data is more structured. The database will provide a consistent use of identifiers, MOD association file loading, tracking when no ortholog found, and an automated response if a paper appears after a 'comprehensive date'. Sohel Merchant (left in July) wrote prototype << ADD URL>>. A new member of staff will start at the end of September to continue development.
Annotation Progress – see slide.
Mary Dolan's tool for comparing annotations by looking at generic GOSlim branches useful as different organisms are used in different experimental approaches and different levels of data are available in different organisms. Eurie: if there is an outlier in annotation consistency checks this might also indicate organism-specific data (e.g. chromatin silencing not appropriate term for yeast).
Table View (slim showing each terms annotated for a gene) includes every term useful for curation and annotation consistency (add link???).
Ontology Development Aim to have robust discussions on annotation and ontoloo9gy development issues. Number of sourceforge requests from reference genome group in the hundreds over 16 months. There is an average of 10-12 SourceForge requests per month. GO editorial group doing a good job at keeping up with these. Existing requests are problematic. 411 terms. - It is important that curators label their SourceForge request as relating to a Reference Genome group.
MH: Can retrieve number of GO terms that have resulted from these requests by looking at the cross-references file: 411 terms from Reference Genome-marked reqests.
Ruth Lovering's Metrics Document v3: File:HowToCaptureMetrics3.doc
Publicising - need to start publicizing Reference Genome work.
Annotation Outreach – Jen Deegan
Aim: to find new groups to join the GOC annotation effort, and keeping track of new groups annotating and writing documentation to help get groups started.
Jen described the scope and techniques of outreach effort. Showed an 'ontology ' of outreach effort. There has been much progress on grants.
Attending many regular conferences.
Less cold calling, it wasn’t very successful. More luck tracking down the right person at conferences. Responding to invitations.
People going to meeting – report back information from willing people to Jen.
The SOPs have been tricky but are now on the public GOC website:
http://www.geneontology.org/GO.annotation.SOP.shtml MA: this page is difficult to find. Action: this page needs to be reviewed and included in the next newsletter
ACTION ITEM Jen: A reference to these pages should go in next newsletter.
ACTION ITEM Jen Add a link from outreach to the SOPs)
There has been funding success - for the British Heart Foundation and AgBase grants.
MA: for new groups annotating, how many SourceForge requests are we getting? e.g. Aspergillus group should have requested new terms?
SL: agree. As soon as an annotation effort really has started, the group often needs a number of new terms.
Jen: for emerging genomes the main problem is finding funding to support an annotation effort.
MC: need to determine if they are only doing IEA annotation, or whether they have the time to carry out manual curation.
JH: the process of making new term requests is not obvious
JW: the SourceForge term tracker only goes to the GO list, so other groups not aware
MH: it is possible to add more e-mail addresses to this list.
MA: not our job to source funding for new groups, it is the job of the individual groups.
JB: supporting new groups is important, need to mentor groups and support them submitting new terms.
ACTION ITEM investigate why terms requests aren’t coming in, do we need to do things to make it easier, SF tracker list/annotation list/ who are on these lists/ do other people need to be on those lists?
User Advocacy - Eurie
Focusing on lines of communication, web presence, newsletter and mailing list.
Different users, new users, current users, power users
Most of the past year has focused on the lines of communication.
wiki User Advocacy main page: http://gocwiki.geneontology.org/index.php/User_Advocacy
Rota of mailing list monitors.
Newsletters archived. Future news items page on wiki. Wiki or Newsletter ideas <<add link>>
Michael A wants ISSN for the newsletter.
ACTION ITEM NML Michael sent URL to Eurie – Action Eurie!
Somebody mentioned RSS feed, is this a potential action?
Users meetings, we have a page of potential meetings on wiki. - used to target groups new to GO and help education. - have a workshop specific for microarray users (rather than an add-on to MGED)
Tools standards. (Needs to be cleaned up and categorised) - ideas for minimum standards for GO tools - send out list a month ago: http://gocwiki.geneontology.org/index.php/Tools_standards
Production Systems - Ben Hitz
Deployed 4 new linux machines 1 for loading, 2 for AmiGO production, 1 AmiGO development.
Production AmiGO now more fault resistant. ACTION: e-mail Ben if you are not getting a gp2protein check for your database.
Go Database loading speeded up and now in testing.
Godb sequences – using gp2protein files. If possible do all sequences in your DB, not just annotated.
Assocdb fasta file – Header line massive – can be slimmed down?
Association file cleaning – All IEAs must have a with field.
AmiGO – Amelia
AmiGO enhancements and new search features demo
- Search result relevance implemented - most 'relevant' results are shown first
- Term and gene product search is now "intelligent" and AmiGO will automatically search all fields if it doesn't find a match.
- Term enrichment (also known as "GO Term Finder") and GO Slimmer (map2slim) functionality have been added to AmiGO. Both can use uploaded user files or data from the GO database.
- Downloads in OBO, RDF-XML and gene association format now possible
Action Items Review
This large section moved to it's own page:
Afternoon, Sunday, Sept 23, 2007
Reactome - Peter D’Eustachio
Reactome can provide data to proteins that UniProt does not yet have manual annotations for most of this Reactome data is derived from experimental evidence identified from papers however unlike the GO annotation method, the types of experiments have not been recorded.
Emily: GOA would love this data, but unless have a new parent ‘Experimental’ code, the best that exists is ‘TAS’.
Suzi Lewis: there is a use for a hierarchy of evidence codes. With an ‘E’ Experimental code as a parent of the IMP, IGI, IDA, IPI, IEP granular codes.
Peter: Homolog sets used to transfer data between species is determined by individual experts, and transfer between orthologs AND homologs (where functionally similar)
Judy and Suzi: Reactome data is valuable. It is unacceptable to not be including it in GO and it is unacceptable that this data should have anything less than an experimental evidence code. TAS or NAS evidenced data are unacceptable also.
Peter: current Reactome curation methods is to avoid unpublished data and Reactome curators also want to be opinionated about the published data, to the end that Reactome will reflect current expert opinion, and avoiding hypothetical theories. Only confirmed, accepted knowledge is included. There are 10 curators, only 2 of whom have previous experience in GO annotation, there is no budget to do GO annotation and no desire to teach curators about GO evidence codes. Don’t always know which piece of literature applies to which info. 2000 gene annotated. 4000 pieces of literature. It is not clear how many GO annotations this would convert to.
Suzi Lewis: This brings up the question of what is the purpose of evidence codes? Why do we have the ones we have? Do users use them? (something to discuss tomorrow).
Pascale: have evidence from users that they do care whether IDA or IMP codes are used.
Peter: There is not always a 1 GO term to 1 publication relationship. Sometimes a GO term may have originated from the combined curation of many papers.
Eurie and John Day-Richter: TAS annotations are valuable, and may be good to get the data in.
Suzi, Judy: this data is too good for TAS.
Emily D: Why not use a mix of codes depending on the GO term to publication ratio? For those instances where there is a 1:1 relationship of GO term to publication: use ‘E’, for 1 GO term to many publications: use ‘TAS’ and cite the Reactome reaction web page as the source – this then acts as the reviewed document.
David Hill: concerned about the proposition of a new ‘Experimental’ evidence code: might loose analytic power.
Judy B: could Reactome curators go back and re-annotate those 4,000 papers and convert the codes to one of the GO experimental codes? This would only take 2 weeks to do.
Peter: Not possible – Reactome have defined goals, we cannot afford to reannotate for GO. 75 genes/month is the absolute minimum annotations. We have our own grant objectives we must fulfill.
David Hill: GO curators could prioritize the reannotation of genes for which there is not much annotation available.
Rex: could the reference genome groups each take on a subset of annotations and re-annotate?
Emily: then the annotation would belong to the group that reannotated. We would be using Reactome data as a source, but the final annotations would be attributed to the group that provided the final annotations. Might not be the best use of resources.
Suzi : Would accept ‘EXP’ for the 1:1 mapping of GO term to publication.
Q Val: Any idea how many aren’t covered by GO annotation already? A. No…
Judy, Sue R, Emily D, Tanya B: the ‘EXP’ code would make life easier for users, for other integrations as well
ACTION: Reactome annotations should be available from GO by the next GO Consortium meeting. Chris, Alex, Jen and Ruth to be responsible. Add new evidence code EXP for 1:1 Reactome to literature, add all other Reactome with TAS to Reactome source.
Arguments for structuring evidence codes i) make things simpler ii) allow incorporation of other date iii) needn't change our current usage iv) do the TAS for the things that don’t fall under EE that can’t be assigned to a single paper.
(continue tomorrow the discussions of the point of evidence codes and the possibility of new parent ‘EXP’ code)
Protein Complexes: GO vs/ Reactome
Reactome complexes are seen as an entity, (i.e. a collection ofo proteins) whereas GO treats complexes as a subcellular location However there is also a blurring between the two for Reactome, especially when looking at large complexes. Peter: In our annotations, a cross-reference slot allows us to cite a GO identifier for the location (usually to the parent term of the complex). Reactome curators add the cc term that is most granular, and willing to generate SourceForge request for those missing
Judy B: talked to Lisa in Bar Harbor on complexes for Reactome. Concern about the active function tag to the active polypeptide.
Peter: for a catalysis – any physical entity in a complex is given a GO term describing the activity, however the active unit, which mediates the reaction is labeled by Reactome. Can parse out which of the polypeptides had the catalysis functions and which are just associated – in most cases this is identified by experimental data. Although Reactome does not always search for the most granular Biological Process GO term, these haven’t been applied consistently.
David Hill: there should be no problem mapping this data from Reactome, while the concepts in GO and Reactome are not equivalents this is not a problem as GO would annotate the same gene products as Reactome would.
Peter: Ewan did have a concern about the ‘contributes_to’ qualifier – concerned that a significant number of end users would not always be aware of use contributes_to. But really this is the users problem. And they can strip out if necessary.
Jennifer: users have suggested that GO could strip out annotations which use the contributes_to column (especially the NOT annotations) and these then could be provided as a separate file. As these can be dangerous to ignore.
ACTION ITEM convert Reactome complex terms to GO terms
‘Taxon and GO’ - Jen Deegan
File:Taxon and GO GOC PU 2007.ppt (using paper from Waclaw Kusnierczyk)
Originally Chris and Jen worked to loose sensu tags and redefining definitions and adding taxon links - However removal of taxon has been a problem. There are now 23,802 terms. Searching for terms is a time sink for users, - GO help has often received queries from users asking if there is a taxon-specific GO slim/subset of terms (e.g. plant-specific GO)
- In addition, Jen as outreach officer has found new MOD groups are unwilling to annotate to GO unless there is a slim available for them.
- GO language can be subtle. GO term names can now be complex now the sensu information has been removed. This would make GO terms easier to find and decipher.
- In addition, having taxon information in the GO helps error checking
- There are 3 types of relationships that could be applied to relate taxon to GO terms: 1. Is_relevant_to ` 2. is_only_in 2. applies_to_all
This taxon-specific information would be added into a separate file.
Judy: Against including taxon information within the GO as we do not know all properties of a taxon. Taxonomic information is in flux also, we do not want a dependence on taxonomy in GO. We would be restricting ourselves if we did not make all terms available to all users. Could not instead users look at the terms that were used by a reference genome group to see what terms are appropriate for a particular taxon?
- general disagreement from curators of this possibility.
Agreement that there are incorrect annotations which relate to taxon-specific properties: Harold: in the Phantom load – needed to remove incorrect mouse annotations
Val, Harold: InterPro2GO throw out problems. These could be identified by this method.
Val: I perform monthly checks to ensure no inappropriate terms have come in at high level. This is time consuming, and this would help.
Pascale: would help sanity check annotation data
Val: this species information doesn’t need to be comprehensive to be useful for annotation checks
Eurie: if this would help annotators, this information could be built into an annotation tool?
Ruth: there are interesting concepts here, but does it need to be so complicated, would all taxons need to be included. Could we not instead just use just 10 high-level taxon identifiers.
Judy: Instead, could not rulebase triggers be used Efforts should be on annotation of literature rather than waste a considerable amount of time incorporating taxon information. We do not want to commit such a level resources to such a project especially as budgets are stretched presently. Again, concern about fluidity of taxon-specific information
Sue Rhee: we should explore usage of GO slims.
Suzi Lewis: there are risks in this kind of project, and concerned that this project would entail quite a bit of work and could also be misunderstanding by users. Can we have a low-key evaluation.
JDR: a large-scale activity of this – is a bad idea. You would propagate garbage by accepting all annotations. Could use as just a framework by only using 10 top taxon id. – this would already help find problems. JC – agreed.
Alex D: Isn’t this just a user education problem? Users need to take the time to understand the GO hierarchy, that you can search synonyms, definitions etc. Feel that user queries are symptoms of users not trying hard enough to work with GO.
Mike Cherry: could not afford to make this a big project, there are other developments in GO which need to be addressed
Rex: Had concern about making taxon-specific assertions that are flawed. If these types of sanity checks or limits were automatically applied, we would loose the potential value of not looking into these, however this data would probably tell us something fundamental about biology, and loose the ability to investigate these.
Judy: classifications of taxon are based on phenotypes and not molecular data and many things are being found and taxons are being redefined. Prefers’ is_relevant_to’ Like the idea of flags/triggers to factiliate work, but wouldn’t automatically exlude, as this data is important.
Michael A: while some taxonomy is changing e.g. in protista, it is unlikely that viridplantea or mammalian will move around so much.
Ben Hitz: what fraction of problems would be solved if there were cross-products to taxonomy were included?
Jen Deegan: it would solve some, it would help with the development terms.
Ben Hitz: what would the time line be for taxon cross-products?
Chris Mungall: this is much further down the line.
Judy. Our main issue here is how to facilitate annotations in our groups. However but we are hung up on a suggestion from outside the group.
Chris Mungall: slims are much harder to maintain than these relationships would be.
Michelle M: When the prokaryotic subset was created, she was v much against. Instead of users looking at 20,000 terms, they are now looking at 9,000 – there is not that much benefit. Don’t think new users need this, need to facilitate better ways of finding terms within the tool. For curators it might be useful for error checking, but not new users.
JDR: although there is a big concern that you’d loose annotations because of these relationships, this would not be the case as the incorrect annotations would instead be brought to your attention – and visible to better investigate/ or improve GO. the rules could be fixed.
Ruth: how would this data be viewed ? In addition, if a user does not understand a term then it really is a problem with the terms definition – instead the definition needs to be improved, this would be far more valuable than adding in an additional cross-link.
Jen: will be willing to carry out a small pilot version of this task in her own time. Would add 10 is_only _in relationships and use these and the annotations to check for errors in the annotations and the ontology structure.
ACTION: Jen to do a pilot project with a minimal set of terms, as an experiment and bring back results for next GO meeting
ACTION: (David Hill) Make difficult sensu terms organism specific (biologist intuitive) (i.e plant vacuole, fungal vacuole). However GO definitions will still be designed to be formal, not depending on species to define the term.
Summary of action Items from Day 1
- Tutorial on wiki discipline (assigned to Jim Hu ?).
- (ALL) Look at and comment on outstanding items Outstanding Action Items from 17th GOC Meeting, Cambridge UK
- Check whether there should be a relationship between pigment metabolic process and pigmentation
- Jen: A reference to these pages should go in next newsletter.
- Jen Add a link from outreach to something (SOP?)
- investigate why terms requests aren’t coming in, do we need things we need to do to make it easier, SF tracker list/annotation list/ who are on these lists/ do other people need to be on those lists?
- NML Michael sent ISSN URL to Eurie – Action Eurie!
- e-mail Ben if you are not getting a gp2protein check for your database.
- Somebody mentioned RSS feed, is this a potential action?
- Reactome annotations should be available from GO by the next GO Consortium meeting. Chris, Alex, Jen and Ruth to be responsible. # Add new evidence code EXP for 1:1 Reactome to literature, add all other Reactome with TAS to Reactome source.
- Convert Reactome complex terms to GO terms
- Jen to do a pilot project with a minimal set of terms, as an experiment and bring back results for next GO meeting
- (David Hill) Make difficult sensu terms organism specific (biologist intuitive) (i.e plant vacuole, fungal vacuole). However GO definitions will still be designed to be formal, not depending on species to define the term.