GO wiki (new pages)

Subscribe to GO wiki (new pages) feed
From GO Wiki MediaWiki 1.27.0
Updated: 54 min 44 sec ago

Ontology meeting 2017-12-18

15 hours 36 min ago

David: Created page with "= Conference Line = *Zoom: https://stanford.zoom.us/j/828418143 = Agenda = ==Holiday Schedule== David will be taking time off between Christmas and New Years' but he will c..."

= Conference Line =

*Zoom: https://stanford.zoom.us/j/828418143

= Agenda =

==Holiday Schedule==
David will be taking time off between Christmas and New Years' but he will continue to maintain the GH Rota during that time. Please let him know if you will be unavailable.

==Special Presentation==
Bill Baumgartner will present the work he has been doing to align OBO ontologies. This will take the first 30 minutes of the meeting.

==GH project link==
https://github.com/geneontology/go-ontology/projects/1

== Editors Discussion ==
The GH ticket-closing jamboree will be from Feb. 12-16th in Denver.


= Minutes =
*On call:



[[Category: Ontology]]
[[Category: Meetings]] David
Categories: GO Internal

DictyBase December 2017

Wed, 12/13/2017 - 13:26

Pfey03: Created page with "== dictyBase, December 2017 == === 1. Staff working on GOC tasks === PI: Rex Chisholm Annotators: Petra Fey, Robert Dodson Developer: Siddhartha Basu All dictyBase staff..."

== dictyBase, December 2017 ==

=== 1. Staff working on GOC tasks ===

PI: Rex Chisholm

Annotators: Petra Fey, Robert Dodson
Developer: Siddhartha Basu

All dictyBase staff contribute to GO activities. This is currently a total of 3 FTE positions. We do not receive specific funding for the GO.


=== 2. Annotation progress ===

The total annotations includes all, including IEAs from GOA. The non-IEA annotation numbers also include annotations that are not from dictyBase, mainly those from the PAINT project (40% and a few from INTACT and UniProt (3%), while dictyBase contributes 57%. The experimental annotations are nearly all assigned by dictyBase (98%) and the indicated annotation extensions have been exclusively annotated by dictyBase curators.


{| border="1" cellspacing="0" cellpadding="5" align="center"
!
! Dec 2016
! Dec 2017
! % Change
|-
| '''Total GO Annotations'''
| 68587
| 70697
| +3.1%
|-
| '''Non-IEA annotations'''
| 31081
| 30841
| -0.8% *
|-
|}



=== 3. Methods and strategies for annotation ===




[[Category: Reports]] Pfey03
Categories: GO Internal

Manager Call 2017-12-20

Wed, 12/13/2017 - 07:16

Vanaukenk: /* Documentathon */

= Agenda =

== Documentathon ==
*Before meeting, review as many existing related tickets as possible
*Best practices:
**Have a date last reviewed on every page
*Review web pages under Documentation, FAQ
*Agenda items:
**Annotation guidelines
***Axes of classification for annotation guidelines
****Term usage
****Experiments
***Evidence codes
***Annotation relations
****Need to be clear about the differences between relations used for GP-GO annotation, GO-CAM annotation, and the ontology
****https://github.com/geneontology/go-annotation/issues/1690
****https://github.com/geneontology/go-annotation/issues/1687
****GAF/GPAD
****GO-CAM
***Annotation extensions
***Annotation file pipelines
****https://github.com/geneontology/go-annotation/issues/1683
****https://github.com/geneontology/go-annotation/issues/1682
****https://github.com/geneontology/go-annotation/issues/1674
****Submission SOP
****Error checks and Jenkins jobs/reports
****Dealing with redundant annotations
**Noctua
***User guide
**Readthedocs
***Can we make better use of this?
***Nice example of formatting: http://firefox-puppeteer.readthedocs.io/en/master/index.html
**Using GO - extract whatever we can from the GO handbook
***File formats available
***Annotation basics
***Reference proteomes vs complete proteomes
*Goals/Deliverables
**Highest priorities:
***Public-facing web pages
***Noctua and GO-CAM (need to consolidate and remove links to older documentation)
****Relations
****User guide
****Evidence codes
***File pipelines
****Annotation files
****Ontology files
**New documentation review by expert, new users


[[Category: GO Managers Meetings]] Vanaukenk
Categories: GO Internal

SGD December 2017

Wed, 12/13/2017 - 07:13

Hdrabkin: report

= Overview: =
= 1. Staff: =
Funded via the GOC award during 2U41HG002273-17

J. Michael Cherry, PI

Gail Binkley, SGD Project Manager and DBA

Emily Heald, Biocuration Assistant

Kalpana Karra, Sr. Software Developer

Patrick Ng, Biocuration Assistant


Staff funded via other sources that provided curation or support for the GOC tasks.

Stuart Miyasato, Systems Administrator

Rob Nash, Sr. Biocuration Scientist

Edith Wong, Sr. Biocuration Scientist

Stacia Engel, Sr. Biocuration Scientist

Terry Jackson, Sr. Biocuration Scientist

Kevin MacPherson, Biocuration Assistant

Sage Hellerstedt, Biocuration Assistant


= 2. Annotation Progress =

{| style="border-spacing:0;"
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"|
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| Total by end of 2016
| style="border:0.0069in solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 2017 activity

|-
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| Genes with manual annotations
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 7121
| style="border:0.0069in solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 319 genes annotated

|-
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| Papers with manual annotations
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 10658
| style="border:0.0069in solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 249 papers curated

|-
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| Manual annotations
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 45330
| style="border:0.0069in solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 768 new annotations

|-
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| Genes with HTP annotations
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 3936
| style="border:0.0069in solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| No new HTP annotations

|-
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| Papers with HTP annotations
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 54
| style="border:0.0069in solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| No new HTP annotations

|-
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| HTP annotations
| style="border-top:0.0069in solid #000000;border-bottom:0.0069in solid #000000;border-left:0.0069in solid #000000;border-right:none;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| 8308
| style="border:0.0069in solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"| No new HTP annotations

|}
'''3. Methods and strategies for annotation'''

''(please note % effort on literature curation vs. computational annotation methods)''


# ''Literature curation: 95%''

Literature curation continues to be the major focus of SGD’s GO annotation efforts. GO annotation is a core task provided by all curators, as well as some of the curation assistants. SGD continues to enhance our curation process as defined by the GOC. We have also begun to train the team on the use of the LEGO editor Noctua.


# ''Computational annotation strategies:'' ''5%''

1. Yeast genes manually curated by other groups (including UniProt and GO Central) are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.


2. Electronic annotations for yeast genes based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.


# ''Priorities for annotation: ''Annotation priorities are currently set via our ‘Literature Triage’ system in which we first evaluate papers for potential GO information. Genes to annotate are then selected based on ‘staleness’ (oldest ‘date last reviewed). Annotations to review are prioritized based on Annotation Consistency activity in the GO GitHub tracker.

'''4. Presentations and Publications'''


a.'' Papers with substantial GO content:''


''N/A''


b. ''Presentations including Talks and Tutorials and Teaching''


Senior Biocuration Scientist Rob Nash presented a tutorial at the [http://meetings.cshl.edu/courses.aspx?course=c-yeas&year=16 Yeast Genetics and Genomics] course at CSHL in late July. He demonstrated the use of YeastMine and how to navigate through SGD's website, including the use of GO annotations provided by SGD.


c.'' Poster presentations''


''N/A''


'''5. Other Highlights:'''


'''A. Ontology Development Contributions:'''


SGD curators request new terms and participated in ontology-related discussions periodically throughout the past year on an as-needed basis.


=== B. Annotation Outreach and User Advocacy Efforts: ===
We had planned to do more outreach but due an unanticipated staffing change we not able to meet our goals.


= C. Other Highlights: =
Edith Wong and Emily Heald attended the Noctua workshop in Corvallis, Oregon on June 4, 2017.


The SGD Curation Team dedicated June and July 2017 to internal training on the Noctua anntoation tool. For eight consecutive weeks, curators worked independently to generate Noctua models from a designated paper, then came together as a group to discuss using the tool, including annotation philosophy regarding selection of GO terms, relations, and annotation extensions.


SGD curators regularly participate in biweekly GO Annotation and GO Noctua conference calls.


We continue to work with the programming staff at LBNL to transfer the geneontology.org resources to AWS. At that time the LBNL staff would take over management of those services. Progress is being made on this front, but the necessary changes have been delayed because of other staffing demands on the LBNL staff. Thus SGD continues to provide systems and programming support for geneontology.org services. Hdrabkin
Categories: GO Internal

ZFIN December 2017

Tue, 12/12/2017 - 10:17

Dhowe: Created page with "Category:ZFIN Category:Reports = Zebrafish Model Organism Database Summary, December 12, 2017 = =BEING UPDATED...NOT YET COMPLETE= = Overview = ZFIN is the Zebrafi..."

[[Category:ZFIN]] [[Category:Reports]]
= Zebrafish Model Organism Database Summary, December 12, 2017 =

=BEING UPDATED...NOT YET COMPLETE=

= Overview =
ZFIN is the Zebrafish Model Organism Database (zfin.org). We serve as the distributor for all GO annotations for the zebrafish, Danio rerio. We make annotations during curation of published papers, and we also load gene_association files from external sources that include Danio rerio annotations. Those are then captured in the ZFIN database, and represented in our gene_association.zfin file for anyone to download and use. These data are checked in to the central GO Consortium repository on a weekly basis.

= Staff: =
{| cellspacing="0" cellpadding="4" align="left"
! style="background:lightgray; width:100px;" | Name
! style="background:lightgray; width:200px;" | Position Type
! style="background:lightgray; width:250px;" | FTE for GO
|-
|style="border-bottom:1px solid lightgray;" valign="top" | Doug Howe
|style="border-bottom:1px solid lightgray;" valign="top" | Data Curation Manager <br/>Principle GO contact at ZFIN
|style="border-bottom:1px solid lightgray;" valign="top" | 0.2
|-
|style="border-bottom:1px solid lightgray;" valign="top" | Sabrina Toro
|style="border-bottom:1px solid lightgray;" valign="top" | Curatorial <br/>GO lead
|style="border-bottom:1px solid lightgray;" valign="top" | 0.2
|-
|style="border-bottom:1px solid lightgray;" valign="top" |6 Curators
|style="border-bottom:1px solid lightgray;" valign="top" |Curatorial
|style="border-bottom:1px solid lightgray;" valign="top" |Variable; ~0.1 each; 0.6 in aggregate
|-
|style="border-bottom:1px solid lightgray;" valign="top" |6 Technical
|style="border-bottom:1px solid lightgray;" valign="top" |5 Developers, 1 DBA
|style="border-bottom:1px solid lightgray;" valign="top" |Variable; ~0.1 in aggregate
|}

<br style="clear:both;">

No direct funding from GOC NHGRI grant.

= Annotation Progress =

[[File:Screen_Shot_2016-12-22_at_2.19.13_PM.png]]


== Methods and strategies for annotation ==
ZFIN does not have curators dedicated exclusively to GO curation. Our curators work on a prioritized set of the current literature focusing first on new mutants, phenotypes, expression, and Human disease models. Any GO that is found in those papers gets added to ZFIN in the course of curating those papers.

'''''Literature curation:'''''

We curate many data types, including GO, as a routine part of our curation effort focused on the most current publications and seminal early publications. The only real exception to that is when we participate in focused annotation efforts such as those spearheaded by members of the GO consortium, or when we do "back curation" to find important uncharted data when we release new curation capabilities.

'''''Computational annotation strategies:'''''

We continue to align our gene records with UniProt protein records on an approximately monthly basis. At that time, we also apply current versions of the GO translation tables interpro2go, UniProtKW2go, and ec2go to generate electronic annotations in our system. On a monthly basis we also load GO annotations from GOA, PAINT, and computationally inferred GO annotations from function to process or component terms provided by the GOC. In some cases the resulting new annotations in ZFIN are electronic in origin, particularly from GOA (sub cellular location for example).


'''''Priorities for annotation:'''''

Our curation priority remains focused on keeping up with the current zebrafish literature, focusing first on papers with new mutants, phenotypes, expression, and Human disease models. We consider this to be "paper-centric" curation. Though many of these papers do contain GO annotations, we do not currently prioritize our curation on the basis of their potential GO content. When GOC members ask us to participate in a focused annotation effort we do make an effort to participate as fully as possible in the required "gene-centric" GO curation.

= Presentations and Publications =


= Ontology Development Contributions =



= Annotation Outreach and User Advocacy Efforts =

= Other Highlights =
GAF files are currently checked into the GO SVN repository on a weekly basis. We rely largely on QC reports that come from the GO GAF validation steps after file check-in. We also have internal processes that monitor annotations for use of obsolete or secondary GO term usage in annotations. Sabrina Toro, a ZFIN curator, continues with the primary responsibility for weekly submission of our GAF and gp2protein files in consultation with Doug.

Doug and Sabrina attended the GO meeting and subsequent Noctua workshop given at USC in November, 2016.

We are in consultation with Seth and Chris to begin planning steps towards adoption of Noctua for GO curation at ZFIN. Dhowe
Categories: GO Internal

GO-CAM December 13, 2017

Tue, 12/12/2017 - 09:15

Vanaukenk: /* Models Discussion */

= Zoom URL =
https://stanford.zoom.us/j/679970729

= Agenda =
== Updates/Discussion on 1.0 Release Milestones ==
=== Annotation Attribution in GPAD Output Files ===
*[https://github.com/geneontology/noctua/issues/458 noctua github ticket #458 - Attribution with GO-CAM exports to GOC annotation files]
*[https://github.com/geneontology/noctua/issues/502 noctua github ticket #502 - providedBy should be used in GPAD export]
*[https://github.com/geneontology/go-site/issues/453 go-site github ticket #453 - All Noctua curators should have "updated" metadata associated in the YAML file (including group and URI)]
*Issue summary: we want to make sure that, in the GPAD files, attribution in the 'Assigned By' field is correctly populated with a curator's annotation group
*Is this a good time to clean house wrt older or test models?
*Status report:
**Seth has generated a [http://skyhook.berkeleybop.org/snapshot/metadata/users-and-groups-report.txt report] that curators can view to see if they need to make updatesyy
**Most current users and groups seem to be okay
**UniProt will report back on how they want to be represented later this week

=== Allow negation in Noctua and SAE and in GPAD export ===
*[https://github.com/geneontology/noctua/issues/524 noctua github ticket #524 - Allow negation in Noctua and SAE and in GPAD export]

=== export-lego-to-gpad-sparql should collate by MOD ===
*[https://github.com/geneontology/go-site/issues/431 go-site github ticket #431 - export-lego-to-gpad-sparql should collate by MOD]

=== Models Discussion ===
*Restrict this call to technical issues?
*Start more rigorous models discussion on the annotation call?
*Discuss models and issues amongst a smaller curation working group first?

= Minutes =
*On call:

[[Category: Annotation Working Group]] Vanaukenk
Categories: GO Internal

WormBase December 2017

Tue, 12/12/2017 - 05:47

Vanaukenk: /* Annotation Progress */

Overview:

= Staff =

Person, Group [Effort, Funding]

Paul Sternberg, PI, WormBase, GO [8%; 0% funded by GOC]

Valerio Arnaboldi, Developer, Textpresso [%; % funded by GOC]

Juancarlos Chan, Developer, WormBase [25%; 25% funded by GOC]

Sibyl Gao, Developer, WormBase [5%; 0% funded by GOC]

Kevin Howe, Project Lead, WormBase - EBI [5%; 0% funded by GOC]

Raymond Lee, Curator, WormBase [10%; 0% funded by GOC]

Hans Michael Mueller, Project Lead, Textpresso [75%; 50% funded by GOC]

Daniela Raciti, Curator [10%; 0% funded by GOC]

Kimberly Van Auken, Curator, Co-Manager, Annotation Working Group [100%; 75% funded by GOC]

= Annotation Progress =

'''WormBase GO Annotation Statistics as of December 12, 2017'''

Manual annotation statistics are summarized in Tables 1 - 3.

Total number of unique manual annotations: 44211 (+3.4% from 2016)

Total number of genes with manual annotations: 7484 (-1.5% from 2016)

'''Table 1: Summary of ''C. elegans'' Manual Biological Process Annotations'''

'''Numbers refer to total number of annotations; annotations in parentheses represent annotations with extensions.'''
{| class="wikitable" style="text-align:center"
{| border="1" cellpading="2"
|-
! Annotation Group !! IMP !! IGI !! IDA !! ISS !! TAS !! IEP !! IPI !! IC !! NAS !! ISM !! ND !! IBA !! IRD
|-
! WormBase
| 7623 (426)|| 3141 (90) || 1106 (24) || 327 (1) || 109 || 292 (56) || 51 || 52 (10) || 32 || 2 || 2 || 0 || 0
|-
!UniProt
|1530 (552) || 976 (390) || 165 (15) || 197 || 26 (3) || 14 || 2 (2) || 5 || 104 || 0 || 65 || 0 || 0
|-
!CACAO
| 20 || 1 || 3 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!BHF-UCL
| 11 || 0 || 0 || 2 || 0 || 4 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!MGI
| 4 || 0 || 6 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!HGNC
| 0 || 0 || 0 || 4 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!GO_Central
| 2 || 0 || 0 || 4 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 7945 || 1
|-
!ParkinsonsUK-UCL
| 10 (4) || 6 (3) || 11 || 2 (1) || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!Totals
| 9200 (982) || 4124 (483) || 1291 (39) || 536 (2) || 135 (3) || 310 (56) || 53 (2) || 57 (10) || 136 || 2 || 67 || 7945 || 1
|}



'''Table 2: Summary of ''C. elegans'' Molecular Function Annotations'''

'''Numbers refer to total number of annotations; annotations in parentheses represent annotations with extensions.'''
{| class="wikitable" style="text-align:center"
{| border="1" cellpading="2"
|-
! Annotation Group !! IMP !! IGI !! IDA !! ISS !! TAS !! IPI !! IC !! NAS !! ISM !! ND !! IBA !! ISO !! IKR !! IRD
|-
! WormBase
| 161 (11) || 32 || 1688 (209) || 647 (4) || 45 || 1348 (5) || 21 (1) || 4 || 3 || 73 || 0 || 2 || 0 || 0
|-
!IntAct
| 0 || 0 || 0 || 0 || 0 || 2085 (52) || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!UniProt
| 57 (2) || 17 || 139 (3) || 194 || 23 (1) || 321 (3) || 4 || 51 || 0 || 126 || 0 || 0 || 0 || 0
|-
!CACAO
| 1 || 0 || 7 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!GO_Central
| 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 6538 || 0 || 1 || 1
|-
!HGNC
| 0 || 0 || 0 || 2 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!ParkinsonsUK-UCL
| 0 || 0 || 0 || 0 || 0 || 2 (2) || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!Totals
| 219 (13) || 49 || 1834 (212) || 843 (4) || 68 (1) || 3754 (60) || 25 (4) || 55 || 4 || 199 || 6538 || 2 || 1 || 1
|}


'''Table 3: Summary of ''C. elegans'' Cellular Component Annotations'''

'''Numbers refer to total number of annotations; annotations in parentheses represent annotations with extensions.'''
{| class="wikitable" style="text-align:center"
{| border="1" cellpading="2"
|-
! Annotation Group !! IMP !! IGI !! IDA !! ISS !! TAS !! IPI !! IC !! NAS !! ISM !! ND !! IBA
|-
! WormBase
| 9 || 0 || 5863 (784) || 382 || 27 || 141 (3) || 50 || 7 || 4 || 10 || 0
|-
!GO_Central
| 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 6326
|-
!UniProt
| 29 (10) || 1 || 379 (73) || 203 || 18 || 0 || 19 || 50 || 0 || 118 || 0
|-
!MGI
| 0 || 0 || 16 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!HGNC
| 0 || 0 || 0 || 8 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
! BHF-UCL
| 0 || 0 || 7 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!CACAO
| 0 || 0 || 3 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0
|-
!Totals
| 38 (10) || 1 || 6268 (857) || 593 || 45 || 141 (3) || 69 || 57 || 4 || 128 || 6326
|}


'''Table 4: Summary of ''C. elegans'' Computational Annotations'''

Summary Statistics Based on WormBase Release WS256

Genes Stats:
Genes with GO_term connections 15047
Non-IEA-only annotation 640
IEA-only annotation 7830
Both IEA and non-IEA annotations 6577

GO_term Stats:
Distinct GO_terms connected to Genes 5679
Associated by non-IEA only 3123
Associated by IEA only 825
Associated by both IEA and non-IEA 1731

{| class="wikitable" style="text-align:center"
{| border="1" cellpading="2"
|-
! Type of Annotation !! IEA
|-
!Phenotype2GO Mappings - WormBase
| 37,714
|-
!IEA/InterPro2GO - WormBase
| 22,660
|-
|}


[[Category:Reports]]

= Methods and strategies for annotation =

==Curation methods==

===Literature curation===

Curation of the primary literature continues to be the major focus of our manual annotation efforts.

Over the past year, WormBase curation efforts were focused largely on developing preliminary pathway models using the Noctua curation tool. To this end, literature curation involved reviewing ''C. elegans'' pathways, the biological entities that participate in those pathways, and the annotations, particularly Molecular Function annotations, associated with those entities. Pathways reviewed include apoptosis, asymmetric cell division, defense response, insulin signaling, neuronal cell fate specification, mRNA decay, semaphorin/plexin signaling, thermosensory transduction, and TOR signaling.

===Curation using the Textpresso information retrieval system===

We also employ the Textpresso information retrieval system for curation of GO Cellular Component and Molecular Function annotations.

===Computational annotation strategies===

Our computational annotation strategies include mapping genes to GO terms using InterPro domains performed as part of the WormBase build cycle, as well as computational predictions made via the UniProtKB pipeline, including keyword mappings and UniRule mapping.
Also as part of the WormBase build cycle, we map genes to Biological Process terms based upon mappings between terms in the Worm Phenotype Ontology (WPO).

==Curation strategies==

===Priorities for annotation===

Selection of genes for annotation is guided by several criteria:

*Annotation of gene sets involved in specific biological processes as part of the LEGO working group
*Genes identified in Textpresso-based curation pipelines, for example genes described in papers flagged by an SVM (Support Vector Machine) classification algorithm having a high confidence of reporting Molecular Function experiments such as enzymatic assays
*Re-annotation of genes affected by changes to the ontology, e.g. cilia biology, ubiquitination, enzyme regulator activities, and obsoleted annotation extensions
*Publication of newly characterized genes for which no previous biological data was available

= Presentations and Publications =
==Papers with substantial GO content==
*Expansion of the Gene Ontology knowledgebase and resources. Gene Ontology Consortium. Nucleic Acids Research (2016) pii:gkw1108. PMID:27899567
*Guidelines for the functional annotation of microRNAs using the Gene Ontology. Huntley RP, Sitnikov D, Orlic-Milacic M, Balakrishnan R, D'Eustachio P, Gillespie ME, Howe D, Kalea AZ, Maegdefessel L, Osumi-Sutherland D, Petri V, Smith JR, '''Van Auken K''', Wood V, Zampetaki A, Mayr M, Lovering RC. RNA. 2016 May;22(5):667-76. doi:10.1261/rna.055301.115. PMID:26917558.

== Presentations including Talks and Tutorials and Teaching ==
*TextpressoCentral: A System for Integrating Full Text Literature Curation with Diverse Curation Platforms including the Gene Ontology Consortium's Common Annotation Framework. '''Kimberly Van Auken''', Yuling Li, Seth Carbon, Christopher Mungall, Suzanna Lewis, Hans-Michael Muller and Paul Sternberg. ISB 2016 Geneva, Switzerland. https://www.sib.swiss/events/biocuration2016/oral-presentations

=Other Highlights=

== Annotation Outreach and User Advocacy Efforts ==
*Kimberly Van Auken continues to serve on the GO-help rota.
*Kimberly Van Auken served on the Data Capture Working Group.

== Annotation Advocacy ==
* Kimberly Van Auken and David Hill (MGI) continue to serve as Annotation Working Group Co-Managers.
* Kimberly Van Auken continued to participate in the LEGO working group as an alpha tester of the Noctua software and helped to train GO curators in LEGO curation and the Noctua annotation tool at the Geneva LEGO workshop (April, 2016), an MGI workshop (June 2016), an EBI workshop (September 2016), and the USC workshop (November 2016).

== Text Mining and Textpresso Central ==
*Monica McAndrews (MGI), Kimberly Van Auken, Hans-Michael Mueller, and Yuling Li (thru August 2016) are collaborating on a document classification pipeline to help MGI identify papers suitable for curation. Using training and testing papers supplied by MGI, we have developed an SVM classifier to distinguish mouse from non-mouse papers. We are beginning steps to put this pipeline into production.
*Hans-Michael Muller, Kimberly Van Auken, and Seth Carbon continued development of the TextpressoCentral (TPC) curation system and its integration with the Noctua annotation tool. TPC enables curators to perform full text literature searches, view the search results in the context of the paper, annotate text, and send those annotations to an external database. Over the past year, we have worked on developing a curation interface for GO annotation, as well as the protocol for communication between TPC and Noctua

Back to http://wiki.geneontology.org/index.php/Progress_Reports

[[Category: Reports]] Vanaukenk
Categories: GO Internal

Ontology meeting 2017-12-11

Mon, 12/11/2017 - 05:32

David: /* Agenda */

= Conference Line =

*Zoom: https://stanford.zoom.us/j/828418143

= Agenda =

==Holiday Schedule==

==GH project link==
https://github.com/geneontology/go-ontology/projects/1

== Editors Discussion ==
It is looking like the GH ticket-closing jamboree will be from Feb. 12-16th in Denver.

== Editors Guidelines ==

= Minutes =
*On call:



[[Category: Ontology]]
[[Category: Meetings]] David
Categories: GO Internal

RGD December 2017

Fri, 12/08/2017 - 10:40

Slaulederkind: Created page with "== RGD, The Rat Genome Database, December 2017 == === 1. Staff working on GOC tasks === RGD Admin: Mary Shimoyama GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang,..."

== RGD, The Rat Genome Database, December 2017 ==

=== 1. Staff working on GOC tasks ===

RGD Admin: Mary Shimoyama

GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Liz Bolton
(~1.5 fte, 0 funded by NHGRI GOC grant)

IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files:
Jyothi Thota, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)

=== 2. Annotation progress ===

{| border="1" cellspacing="0" cellpadding="5" align="center"
! Gene Products
! Manual Annotations 2016
! Manual Annotations 2017
! % Change
|-
| 19,548
| 52,136
| 53,502
| +2.5%
|-
|}

The number of genes with manual annotations has increased from 6,260 to 6,314(+74, +1.2%).

=== 3. Methods and strategies for annotation ===

Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.

a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2016, there have been 2 major types of gene datasets curated:

# disease related: development-related disease genes, Huntington disease genes, and cancer genes
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.

b. Computational annotation strategies:

# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.

c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.

=== 4. Presentations and publications ===


a. Papers with substantial GO content

# N/A

b. Presentations including Talks and Tutorials and Teaching

# N/A

c. Poster presentations with GO content

# N/A

=== 5. Other Highlights ===

'''A. GO terms and related contributions by RGD'''

RGD has contributed ~105 new terms/synonyms from December 2016 to December 2017.

'''B. Annotation outreach and user advocacy efforts'''


'''C. Other highlights'''

Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu. Slaulederkind
Categories: GO Internal

MGI December 2017

Fri, 12/08/2017 - 06:00

Hdrabkin:

[[Category:MGI]]
Overview:

= Staff: =

[please include FTEs working on GOC tasks designating as well how many FTEs funding by GOC NIHGRI grant]

Judith Blake*

Karen R Christie*

Mary E Dolan

Harold J Drabkin*

David Hill*

Li Ni

Dmitry Sitnikov

<nowiki>* Funded entirely or partially by GO</nowiki>

= Annotation Progress =

{| style="border-spacing:0;"
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| <center>'''Annotation Type '''</center>
| style="border:0.0069in solid #00000a;padding:0.0694in;"| <center>'''Dec 5 2016 '''</center>
| style="border:0.0069in solid #00000a;padding:0.0694in;"| <center>'''replace '''</center>
| style="border:0.0069in solid #00000a;padding:0.0694in;"| <center>'''Change '''</center>
| style="border:0.0069in solid #00000a;padding:0.0694in;"| <center>'''% change '''</center>

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Genes annotated with at least one GO term of any kind
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 24213
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 24224
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -11*
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -0.05

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Annotations:
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 360758
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 362727
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -1969
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -0.54

|-
| colspan="6" style="border:0.0069in solid #00000a;padding:0.0694in;"| '''Total non-IEA Annotation '''

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Number of Genes:
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 24032
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 23979
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 53
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 0.22

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Annotations:
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 278277
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 262218
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 16059
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 6.12

|-
| colspan="6" style="border:0.0069in solid #00000a;padding:0.0694in;"| '''Annotation by Direct Experiment '''

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| MGI Curated Mouse Genes
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 12624
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 12433
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 191
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 1.54

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| MGI Curated Annotations
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 89907
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 87159
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 2748
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 3.15

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| GOA Curated Mouse Genes:
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 5424
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 5075
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 349
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 6.88

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| GOA Curated Annotations:
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 33530
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 30177
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 3353
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 11.11

|-
| colspan="6" style="border:0.0069in solid #00000a;padding:0.0694in;"| '''Annotation by Orthology '''

|-
| style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Genes Annotated by Orthology
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| 12067
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 11866
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 201
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 1.69

|-
| style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Orthology Annotation
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| 106607
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 102212
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 4395
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 4.30

|-
| style="border:0.0069in solid #00000a;padding:0.0694in;"| Genes Annotated by Human Orthology Load (GOA)
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| 10942
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 10701
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 241
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 2.25

|-
| style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Annotation by Human Orthology Load
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| 71680
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 68129
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 3551
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 5.21

|-
| style="border:0.0069in solid #00000a;padding:0.0694in;"| Genes Annotated by Rat Orthology Load (RGD)
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| 4849
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 4696
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 153
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 3.26

|-
| style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Annotations by Rat Orthology Load
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| 31405
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 30769
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 636
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 2.07

|-
| style="border:0.0069in solid #00000a;padding:0.0694in;"| Genes Annotated by Phylogeny
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| 8153
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 6400
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 1753
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 27.39

|-
| style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Annotations by Phylogeny
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| 29434
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 22522
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 6912
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 30.69

|-
| colspan="6" style="border:0.0069in solid #00000a;padding:0.0694in;"| '''IEA Annotation '''

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Genes with IEA Annotations
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 14815
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 14724
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 91
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 0.62

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total IEA Annotations
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 82481
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 100509
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -18028
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -17.94

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Genes with SwissProt to GO Annotations
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 14440
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 14337
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 103
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 0.72

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total SwissProt to GO Annotations
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 57420
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 56888
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 532
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 0.94

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Genes with Interpro to GO Annotations
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 10d103
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 9966
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 137
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 1.37

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Interpro to GO Annotations
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 24074
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 24408
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -334
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -1.37

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total Genes with EC to GO Annotations*
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 817
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 1709
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -892
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -52.19

|-
| colspan="2" style="border:0.0069in solid #00000a;padding:0.0694in;"| Total EC to GO Annotations *
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 987
| style="border:0.0069in solid #00000a;padding:0.0694in;"| 19213
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -18226
| style="border:0.0069in solid #00000a;padding:0.0694in;"| -94.96

|}
'''<nowiki>* Loss due to EC2GO refactoring (no annotations to EC root terms).</nowiki>'''

= Methods and strategies for annotation =
'''''Literature curation:'''''

Literature curation continues to be the major focus of our annotation efforts.

'''''Computational annotation strategies:'''''

As always, current strategies involve use of translation table to mine SwissProt keywords, InterPro domains, and EC numbers for IEA annotation. These are performed automatically on a nightly basis and require little human intervention.

Harold Drabkin monitors weekly QC reports on manual and automatic annotation stats, and responds to questions about specific annotations as required.

'''''Priorities for annotation'''''

* Isoform curation (Harold, Karen, Protein Ontology project); focusing on genes that have isoforms or whose products are modified, and co-ordinate with the Protein Ontology Protein Complex project.
* Genes with no GO annotation but with literature (Li and Dmitry)
* Genes with only IEA annotation but with literature (Li)
* Genes marked as having GO annotation completed, but now having new literature (Dmitry)
* Genes that have an annotation to one of the three root nodes of GO, but have new literature (David)
* Dmitry has been focused on annotation or miRNAs in MGI
* Annotation of ciliary genes (Karen)
* Annotation of metabolic genes, glycolysis,pyruvate metabolism, and carbohydrate catabolism in general (David)
* Autophagy genes

= Presentations and Publications =
a. Papers with substantial GO content
*High-throughput discovery of novel developmental phenotypes. Dickinson ME, Flenniken AM, Ji X, Teboul L, Wong MD, White JK, Meehan TF, Weninger WJ, Westerberg H, Adissu H, Baker CN, Bower L, Brown JM, Caddle LB, Chiani F, Clary D, Cleak J, Daly MJ, Denegre JM, Doe B, Dolan ME, Edie SM, Fuchs H, Gailus-Durner V, Galli A, Gambadoro A, Gallegos J, Guo S, Horner NR, Hsu CW, Johnson SJ, Kalaga S, Keith LC, Lanoue L, Lawson TN, Lek M, Mark M, Marschall S, Mason J, McElwee ML, Newbigging S, Nutter LM, Peterson KA, Ramirez-Solis R, Rowland DJ, Ryder E, Samocha KE, Seavitt JR, Selloum M, Szoke-Kovacs Z, Tamura M, Trainor AG, Tudose I, Wakana S, Warren J, Wendling O, West DB, Wong L, Yoshiki A; International Mouse Phenotyping Consortium; Jackson Laboratory; Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS); Charles River Laboratories; MRC Harwell; Toronto Centre for Phenogenomics; Wellcome Trust Sanger Institute; RIKEN BioResource Center, MacArthur DG, Tocchini-Valentini GP, Gao X, Flicek P, Bradley A, Skarnes WC, Justice MJ, Parkinson HE, Moore M, Wells S, Braun RE, Svenson KL, de Angelis MH, Herault Y, Mohun T, Mallon AM, Henkelman RM, Brown SD, Adams DJ, Lloyd KC, McKerlie C, Beaudet AL, Bucan M, Murray SA. Nature. 2016 Sep 14;537(7621):508-514. doi: 10.1038/nature19356.

* Hill DP, D'Eustachio P, Berardini TZ, Mungall CJ, Renedo N, Blake JA. Modeling biochemical pathways in the gene ontology. Database (Oxford). 2016 Sep 1;2016. pii: baw126. doi: 10.1093/database/baw126. PMID: 27589964

c. Poster presentations

* Judith A. Blake. Genes, Orthologs, and Human Diseases: How Model Organism Databases and the Gene Ontology Empower Knowledge Discovery. The Allied Genetics Conference (TAGC) 2016, Orlando
*Karen R. Christie. Phylogenetically based Gene Ontology (GO) Annotations using the Phylogenetic Annotation and INference Tool (PAINT.The Allied Genetics Conference (TAGC) 2016, Orlando
* Harold J. Drabkin Functional annotation of proteoforms in the Mouse Genome Database using the Protein Ontology. The Allied Genetics Conference (TAGC) 2016, Orlando
* Li Ni. ‘What Does This Gene Do’: Data presentation in Mouse Genome Informatics for the scientific community including neuroscientists. Neuroscience 2016, San Diego, CA

= Other Highlights: =

A. Ontology Development Contributions:

* David Hill co-led the ontology development group with Melanie Courtot, co-organizing the weekly ontology development calls. Addressed GH requests for ontology terms and improvement, and revamped autophagy part of the ontology with Ruth¹s group, Marc Feuermann and Paola Roncaglia.
* Harold Drabkin is adding new molecular function terms to aid in mapping Metacyc identifiers to GO terms.


B. Annotation Outreach and User Advocacy Efforts:
* The Protein Ontology project continues to provide a web interface (http/pir.georgetown.edu/cgi-bin/pro/race_pro) whereby functional annotation using the GO can be applied to PRO submissions.
* Harold Drabkin continues to serve on the GO-help rota.
* David Hill is now co-managing the annotation group with Kimberly Van Auken (WormBase).


C. Other Highlights:

* Karen Christie serves as the MGI representative on the PAINT curation team. As a member of this team, Karen curates Panther families in PAINT to propagate annotations based on evolutionary relationships. She also files bug reports on PAINT and contribute to the improvement of the PAINT software.

* Mary Dolan: Data analysis and visualization for the MGI GO group. QC for GO-related projects: PRO to MGI mapping, mouse reference proteome, production of GPI and GPA files.<nowiki>*</nowiki>

D. Noctua annotation tool.
*David Hill tested the new Noctua tool for LEGO modeling in GO, including development and design of standards for modeling and began creating production LEGO models. He is now training new annotators in the use of Noctua at 4 international workshops
* David worked with GOC software engineers to generate annotation files that can be loaded into model organism databases and with MGI software engineers to load Noctua-derived annotations into MGI. This included standardization of identifiers that are used as annotation objects in Noctua. He also worked on the standardization of GPAD and GPI files as the new exchange format for traditional GO annotations. MGI is now the first database using Noctua in a production environment. Hdrabkin
Categories: GO Internal

Ontology meeting 2017-12-04

Mon, 12/04/2017 - 05:18

David: Created page with "= Conference Line = *Zoom: https://stanford.zoom.us/j/828418143 = Agenda = ==GH project link== https://github.com/geneontology/go-ontology/projects/1 == Editors Discussion..."

= Conference Line =

*Zoom: https://stanford.zoom.us/j/828418143

= Agenda =

==GH project link==
https://github.com/geneontology/go-ontology/projects/1

== Editors Discussion ==

== Editors Guidelines ==
*Closing old tickets
*When? How?
*It seems an SOP would be helpful here.

= Minutes =
*On call:

== Synaptic vesicle endocytosis ==
*Barbara will modify definition of existing term to be inclusive of more mechanisms
*Then create more specific mechanism-based child terms

== Editors guidelines ==
*What to do with old tickets?
*For some it makes sense to keep, especially if the ticket is wrt an issue that is currently under discussion
*Specific tickets that require feedback but don't get it could be closed - use 'waiting for feedback' label for these
**How long should we wait for feedback?
**Six weeks - first reminder
**Next six weeks - change or close
**All contributors to the ticket should be listed as assignees
**Can automation help with sending reminders?
***Look for the label 'waiting for feedback' and given a certain amount of time would prompt a reminder update to the ticket
***21 open tickets with 'waiting for feedback' label
**https://help.github.com/articles/understanding-the-search-syntax/
**https://github.com/geneontology/go-ontology/issues?q=is%3Aopen+is%3Aissue+label%3A%22waiting+for+feedback%22+sort%3Aupdated-asc
*Use a label to distinguish these tickets - 'won't fix'
*When editors have time, they should try to review old tickets
*Perhaps a jamboree in the future to address old tickets would be helpful

== Adding annotation rules ==
*See https://github.com/geneontology/go-site/tree/master/metadata/rules
*First check existing rule summary to avoid duplication of rules
*Then update the list by adding a new rule
*Generate a pull request and assign to Eric so he can create the rule

== Reasoning over roles in Protege ==
*https://github.com/geneontology/go-ontology/issues/14626
*Does this happen?
*For example, 'cocaine binding' should infer to be a type of 'drug binding'
*Something wrong with the import chain? Is there a relationship missing in the ChEBI import?
*Drugs are not listed as leaf nodes in Protege

== Checking for obsolete terms in external ontologies ==
*We need to make sure external ontologies are kept in sync
*https://github.com/geneontology/go-ontology/issues/14605



[[Category: Ontology]]
[[Category: Meetings]] David
Categories: GO Internal

Annotation Conf. Call 2017-12-12

Thu, 11/30/2017 - 09:23

Vanaukenk: /* github review */

= Meeting URL =
*https://stanford.zoom.us/j/976175422

= Agenda =
== github review ==
*go-annotation tracker is used for issues and project management related to the annotation working group
*Issues:
**Annotation review
**PAINT family review
**Keyword mapping questions
**Questions about annotation practice
**Proposals for annotation guidelines
**Requests for documentation
*Use of labels
**Please always add a label to your issue
**Trying to simplify the list of labels
**Removed some that were overlapping, not applicable to this repo
**Would like to move from using group labels to tracking submission via author
***is:issue author:vanaukenk
*All curators who need to work on an issue should be listed in the Assignee field
**Remove your name from the list when you've addressed or complete the work


[[Category:Annotation Working Group]] Vanaukenk
Categories: GO Internal

2018 Berkeley GO Docathon

Tue, 11/28/2017 - 13:00

Cjm: /* Participants */


= Agenda (Draft) =

Rooms:

153 has been reserved on Tuesday, January 23rd. 248 is reserved for the
other 4 days.

= Logistics =

== Accommodations ==

* http://www.fourpointssanfranciscobaybridge.com/

Getting there:

* [https://www.google.com/maps/dir/Four+Points+by+Sheraton+San+Francisco+Bay+Bridge,+Powell+Street,+Emeryville,+CA/MacArthur+BART+Station,+40th+Street,+Oakland,+CA/@37.8346259,-122.2866117,15z/am=t/data=!3m1!5s0x80857e0870dbdd83:0x571df460c4d9d3cb!4m14!4m13!1m5!1m1!1s0x80857e44a03ff3e3:0xc502416c1c31eb3a!2m2!1d-122.2939195!2d37.8381923!1m5!1m1!1s0x80857de2a98ae50d:0xc5fce433b2157d9f!2m2!1d-122.267047!2d37.8290643!3e3 shuttle from MacArthur BART]

Taxis also available from either MacArthur or Ashby

== Parking ==

We will try to reserve as many spots outside the front entrance as we can. Look for spots that say "GO meeting". if you see one, take it.

If there is none available, don't worry. Park temporarily and grab a parking pass from the person at the gate, you can then park in the garage:

* http://biosciopsatberkeley.lbl.gov/location/aquatic-park-office/

== Meeting Location ==

[http://biosciopsatberkeley.lbl.gov/location/aquatic-park-office/ Berkeley Lab, Aquatic Park Offices]

Lawrence Berkeley National Laboratory (LBNL), Aquatic Park office of Biosciences Operations at Berkeley
Physical address: 717 Potter Street, Berkeley, CA 94710

Meeting room: room 181

=== Travel between hotel and meeting ===

* [https://www.google.com/maps/dir/Four+Points+by+Sheraton+San+Francisco+Bay+Bridge,+Powell+Street,+Emeryville,+CA/717+Potter+St,+Berkeley,+CA+94710/@37.8448697,-122.3011831,15z/data=!3m1!4b1!4m14!4m13!1m5!1m1!1s0x80857e44a03ff3e3:0xc502416c1c31eb3a!2m2!1d-122.2939195!2d37.8381923!1m5!1m1!1s0x80857ef68fea8821:0xeaa3c4e92d0ec6a9!2m2!1d-122.294537!2d37.85145!3e2 Walk, 1.3 miles]
* [https://www.google.com/maps/dir/Four+Points+by+Sheraton+San+Francisco+Bay+Bridge,+Powell+Street,+Emeryville,+CA/717+Potter+St,+Berkeley,+CA+94710/@37.8450306,-122.3024045,15z/am=t/data=!4m14!4m13!1m5!1m1!1s0x80857e44a03ff3e3:0xc502416c1c31eb3a!2m2!1d-122.2939195!2d37.8381923!1m5!1m1!1s0x80857ef68fea8821:0xeaa3c4e92d0ec6a9!2m2!1d-122.294537!2d37.85145!3e3 Free Hollis Shuttle ]
* Taxi/Lyft/Uber

Aim to be at the lab for 9am



== Participants ==

{| {{Prettytable}}
|-
! Name
! Organization
! Comments
|-
| David Hill
| Jackson Laboratory
|
|
|-
| Kimberly Van Auken
| Caltech
| Arriving SFO Monday, 8/14, 5:03PM
|-
| Pascale Gaudet
| SIB Swiss Institute of Bioinformatics
|
|-
|}

LBL:

* Chris Mungall
* Eric Douglass
* Seth Carbon
* Suzi Lewis


[[Category:Meetings]]
[[Category:Protege]] Cjm
Categories: GO Internal

Ontology meeting 2017-11-27

Fri, 11/24/2017 - 07:23

Pascale: Created page with "= Conference Line = *Zoom: https://stanford.zoom.us/j/828418143 = Agenda = ==GH project link== https://github.com/geneontology/go-ontology/projects/1 == Editors Discussi..."

= Conference Line =

*Zoom: https://stanford.zoom.us/j/828418143

= Agenda =



==GH project link==
https://github.com/geneontology/go-ontology/projects/1

== Editors Discussion ==

= Minutes =
*On call:



[[Category: Ontology]]
[[Category: Meetings]] Pascale
Categories: GO Internal

Inferred from Physical Interaction (IPI)

Tue, 11/21/2017 - 12:48

Vanaukenk:

'''IPI: Inferred from Physical Interaction'''

*2-hybrid interactions
*Co-purification
*Co-immunoprecipitation
*Ion/protein binding experiments

Covers physical interactions between the entity of interest and another molecule (such as a protein, ion or complex). IPI can be thought of as a type of IDA, where the actual binding partner or target can be specified, using "with" in the with/from field.

Often it is difficult to tell from the evidence presented in a paper whether an interaction is direct or not. Any in vivo/cell lysate method always has the possibility of a third 'bridge' protein - there are many examples of this happening in, for example, yeast 2-hybrid experiments when yeast proteins have proven essential for interactions between two human proteins to occur. The only methods that show direct evidence of two proteins binding are when the two proteins have been isolated and pre-purified. Ideally, curators should only capture direct interactions however, it is acceptable to curate interactions even if it is not known whether they are direct or not.

Examples where the IPI evidence code should be used:

*Binding assays where it is possible to put an ID corresponding to the specific binding partner that was shown to interact with the entity being annotated should be annotated with the IPI code, not with IDA.
*Annotations to the GO term ‘binding’ (GO:0005488) or ‘protein complex' (GO:0043234), or their child terms, which are supported by the isolation of a complex by co-immunoprecipitation or pull-down assays may use IPI with the ID corresponding to the ‘antibody target' or ‘tagged' subunit in the with/from column.
*The GO term ‘protein binding’ (GO:0005515) should only be used with the evidence code IPI and an identifier in the ‘with’ field. A reciprocal annotation must also be made to indicate the interaction in the opposite direction.
*Annotations to Molecular Functions (except ‘catalytic activity’ GO:0003824 or its child terms, see below) or Biological Processes may be made using IPI and an entry in the ‘with/from’ field in order to indicate the inference that the annotated entity is involved in the process or function because it interacts with another entity that was shown experimentally to be involved in that process or function.

Examples where the IPI evidence code should not be used:

*The GO term ‘protein binding’ (GO:0005515) should not be used to describe an antibody binding to another protein. However, an effect of an antibody on an activity or process can support a function or process annotation, using the IMP code.
*Annotations to the GO term ‘binding’ (GO:0005488), or its child terms, which are supported by binding assays where it is NOT possible to put an ID corresponding to the specific binding partner that was shown to interact with the gene product being annotated should be annotated with the IDA code, not with IPI (see table 1).
*Annotations to the GO term ‘catalytic activity’ (GO:0003824), or its child terms, should not use the IPI evidence code. It is unlikely that enough information can be obtained from a binding interaction to support such an annotation.


'''Table 1. Example annotation where it is not possible to add the interacting partner.'''
{| class="wikitable" style="text-align:center"
{| border="1" cellpading="2"
|-
! DB Object ID !! DB Object Symbol !! GO ID !! DB:Reference !! Evidence Code !! With (or) From
|-
| MGI:2137706 || Actn1 || GO:0051015 (actin filament binding) || PMID:15465019 || IDA || -
|}

[http://wiki.geneontology.org/index.php/Guide_to_GO_Evidence_Codes Guide_to_GO_Evidence_Codes]

[[Category: Annotation]] [[Category:Working Groups]] Vanaukenk
Categories: GO Internal

Inferred from Direct Assay (IDA)

Tue, 11/21/2017 - 12:45

Vanaukenk: Created page with "'''IDA: Inferred from Direct Assay''' *Enzyme assays *In vitro reconstitution (e.g. transcription) *Immunofluorescence (for cellular component) *Cell fractionation (for cellu..."

'''IDA: Inferred from Direct Assay'''

*Enzyme assays
*In vitro reconstitution (e.g. transcription)
*Immunofluorescence (for cellular component)
*Cell fractionation (for cellular component)
*Physical interaction/binding assay (sometimes appropriate for cellular component or molecular function)

The IDA evidence code is used to indicate a direct assay was carried out to determine the function, process, or component indicated by the GO term. Curators therefore need to be careful, because an experiment considered as a direct assay for a term from one ontology may be a different kind of evidence for a term from another of the ontologies. In particular, there are more kinds of direct assays for cellular component than for function or process. For example, a fractionation experiment might provide "direct assay" evidence that a gene product is in the nucleus, but "protein interaction" (IPI) evidence for its function or process.

For transfection experiments or other experiments where a gene from one organism or tissue is put into a system that is not its normal environment, the annotator should use the author's intent and interpretation of the experiment as a guide as to whether IMP or IDA is appropriate. When the author is comparing differences between alleles, regardless of the simplicity or complexity of the assay, IMP is appropriate. When the author is using an expression system as a way to investigate the normal function of a gene product, IDA is appropriate.

Examples where the IDA evidence code should be used:

*Binding assays can provide direct assay evidence for annotating to the xxx binding molecular function terms. (Use IDA only when no identifier can be placed in the with/from column; when there is an appropriate ID for the with/from column, use IPI).
*Assays describing the isolation of a complex by immunoprecipitation of a tagged subunit should use IDA, not IPI. Thus this type of assay can provide IDA for annotation to a component term for the specific complex because it is a direct assay for a complex.
*Transfections into a cell line, overexpression, or ectopic expression of a gene when the expression system used is considered to be an assay system to address basic, normal functions of gene product even if it would not normally be expressed in that cell type or location. If the experiments were conducted to assess the normal function of the gene and the assay system is believed to reproduce this function, i.e., the authors would consider their experiment to be a direct assay, and not a comparison between various alleles of a gene, then the IDA code should be used. This is in contrast with a situation where overexpression affects the function or expression of the gene and that difference from normal is used to make an inference about the normal function; in this case use the IMP evidence code.

Examples where the IDA evidence code should not be used:

*Binding assays where it is possible to put an ID corresponding to the specific binding partner that was shown to interact directly the gene product being annotated should be annotated with the IPI code, not with IDA.
*Transfection into a cell line, overexpression, or ectopic expression of a gene where the effects of various alleles of a gene are compared to each other or to wild-type. For this type of experiment, annotate using IMP.

[http://wiki.geneontology.org/index.php/Guide_to_GO_Evidence_Codes Guide_to_GO_Evidence_Codes]

[[Category: Annotation]] [[Category:Working Groups]] Vanaukenk
Categories: GO Internal

Inferred from Experiment (EXP)

Tue, 11/21/2017 - 12:38

Vanaukenk:

'''EXP: Inferred from Experiment'''

This code is used in an annotation to indicate that an experimental assay has been located in the cited reference, whose results indicate a gene product's function, process involvement, or subcellular location (indicated by the GO term). The EXP code is the parent code for the IDA, IPI, IMP, IGI and IEP experimental codes.

The EXP evidence code can be used where any of the assays described for the IDA, IPI, IMP, IGI, or IEP evidence codes is reported. However it is highly encouraged that groups should annotate to one of the more specific experimental codes (IDA, IPI, IMP, IGI, or IEP) instead of EXP, and all curators directly involved in the GO Reference Genome annotation effort are obliged to use these and not EXP.

The EXP code exists for groups who would like to contribute high-quality GO annotations that are produced from directly associating GO terms to gene products by citing experimental published results, but where the group is unable to fit the appropriate specific experimental GO evidence code to each annotation.

A published reference should always be cited in the reference column, and no value should be entered into the with/from column of EXP annotations.

[http://wiki.geneontology.org/index.php/Guide_to_GO_Evidence_Codes Guide_to_GO_Evidence_Codes]


[[Category: Annotation]] [[Category:Working Groups]] Vanaukenk
Categories: GO Internal

Guide to GO Evidence Codes

Tue, 11/21/2017 - 12:19

Vanaukenk:

*These guidelines are a guide to standard usage of the GO evidence codes.
*Annotators may also find the evidence code decision tree useful in selecting the correct evidence code for an annotation.

= Introduction =
A GO annotation consists of a GO term associated with a specific reference that describes the work or analysis upon which the association between a specific GO term and gene product is based. Each annotation must also include an evidence code to indicate how the annotation to a particular term is supported. Although evidence codes do reflect the type of work or analysis described in the cited reference which supports the GO term to gene product association, they are not necessarily a classification of types of experiments/analyses. Note that these evidence codes are intended for use in conjunction with GO terms, and should not be considered in isolation from the terms. If a reference describes multiple methods that each provide evidence to make a GO annotation to a particular term, then multiple annotations with identical GO identifiers and reference identifiers but different evidence codes may be made.

Out of all the evidence codes available, only Inferred from Electronic Annotation (IEA) is not assigned by a curator. Manually-assigned evidence codes fall into four general categories: experimental, computational analysis, author statements, and curatorial statements.

Use of an experimental evidence code in a GO annotation indicates that the cited paper displayed results from a physical characterization of a gene or gene product that has supported the association of a GO term. The Experimental Evidence codes are:

*[[Inferred from Experiment (EXP)]]
*[[Inferred from Direct Assay (IDA)]]
*[[Inferred from Physical Interaction (IPI)]]
*[[Inferred from Mutant Phenotype (IMP)]]
*[[Inferred from Genetic Interaction (IGI)]]
*[[Inferred from Expression Pattern (IEP)]]

High throughput (HTP) evidence codes may be used to make annotations based upon high throughput methodologies. Use of HTP evidence codes should be carefully considered and follow the GOC's guidelines for their use.

*Add list of HTP evidence codes here

Use of the computational analysis evidence codes indicates that the annotation is based on an in silico analysis of the gene sequence and/or other data as described in the cited reference. The evidence codes in this category also indicate a varying degree of curatorial input. The Computational Analysis evidence codes are:

*[[Inferred from Sequence or structural Similarity (ISS)]]
*[[Inferred from Sequence Orthology (ISO)]]
*[[Inferred from Sequence Alignment (ISA)]]
*[[Inferred from Sequence Model (ISM)]]
*[[Inferred from Genomic Context (IGC)]]
*[[Inferred from Biological aspect of Ancestor (IBA)]]
*[[Inferred from Biological aspect of Descendant (IBD)]]
*[[Inferred from Key Residues (IKR)]]
*[[Inferred from Rapid Divergence(IRD)]]
*[[Inferred from Reviewed Computational Analysis (RCA)]]

Author statement codes indicate that the annotation was made on the basis of a statement made by the author(s) in the reference cited. The Author Statement evidence codes used by GO are:

*[[Traceable Author Statement (TAS)]]
*[[Non-traceable Author Statement (NAS)]]

Use of the curatorial statement evidence codes indicates an annotation made on the basis of a curatorial judgement that does not fit into one of the other evidence code classifications. The Curatorial Statement codes are:

*[[Inferred by Curator (IC)]]
*[[No biological Data available (ND) evidence code]]

All of the above evidence codes are assigned by curators. However, GO also used one evidence code that is assigned by automated methods, without curatorial judgement. The Automatically-Assigned evidence code is:

*[[Inferred from Electronic Annotation (IEA)]]

Evidence codes are '''not''' statements of the quality of the annotation. Within each evidence code classification, some methods produce annotations of higher confidence or greater specificity than other methods, in addition the way in which a technique has been applied or interpreted in a paper will also affect the quality of the resulting annotation. Thus evidence codes '''cannot''' be used as a measure of the quality of the annotation.



[[Category: Annotation]] [[Category:Working Groups]] Vanaukenk
Categories: GO Internal

GO-CAM November 22, 2017

Mon, 11/20/2017 - 08:52

Vanaukenk: Created page with "= Zoom URL = = Agenda = = Minutes = *On call: Category: Annotation Working Group"

= Zoom URL =

= Agenda =

= Minutes =
*On call:



[[Category: Annotation Working Group]] Vanaukenk
Categories: GO Internal

Ontology meeting 2017-11-20

Fri, 11/17/2017 - 10:41

Vanaukenk: /* Editors Discussion */

= Conference Line =

*Zoom: https://stanford.zoom.us/j/828418143

= Agenda =
== Documentation on Asserted Parents ==
*Deleting asserted parents was already included in the section on [https://github.com/geneontology/go-ontology/blob/master/docs/CreateNewTerm.md CreateNewTerm].
*Does it need to be somewhere else?
*Is it not clear enough?
==GH project link==
https://github.com/geneontology/go-ontology/projects/1

== Editors Discussion ==
*[https://github.com/geneontology/go-ontology/issues/14579 GO:0043683 type IV pilus biogenesis parentage]
**cellular component assembly vs biogenesis vs morphogenesis - any guidelines for deciding when to instantiate which terms?

= Minutes =
*On call:





[[Category: Ontology]]
[[Category: Meetings]] Vanaukenk
Categories: GO Internal