ImmPort Ontology Conference: Difference between revisions

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'''Where:''' Stanford University
'''Where:''' Paul Berg Hall A #230, [https://maps.google.com/maps?q=Li+Ka+Shing+Center+for+Learning+and+Knowledge&ie=UTF-8&ei=R2MWUreRB5DK9QTUloGoBg&ved=0CAoQ_AUoAg Li Ka Shing Center for Learning and Knowledge], 291 Campus Drive West, Stanford School of Medicine, Stanford, CA 94305.


'''When:''' September 4-5, 2013
'''When:''' September 4-5, 2013


'''Audience:''' The conference is divided into two parts. Day 1 is intended for all those engaged in information-driven immunology research who have an interest in ontology and data standardization; Day 2 is intended to provide training for those interested in acquiring skills needed for working with ontologies to solve specific problems.
'''Audience'''
*Day 1 is intended for all those engaged in information-driven immunology research who have an interest in the work of ImmPort and/or in ontology and data standardization
*Day 2 (by invitation only) is intended primarily for those interested in CyTOF and related issues of data management in immunological science.  


'''Participation:''' There is a limited number of places available for this meeting. If you are interested in attending please contact [mailto:phismith@buffalo.edu Barry Smith] as soon as possible.
'''Background resources'''
*An overview of ontologies proposed by ImmPort for use across the immunology research community is provided  [http://ncorwiki.buffalo.edu/index.php/Immunology_Ontologies here]


'''Goals (tentative)''': The goal of Day 1 is to survey the ontology work being done in support of NIAID-DAIT funded information-driven science, with special emphasis on
If you are interested in attending please contact [mailto:phismith@buffalo.edu Barry Smith] as soon as possible.
*identifying the ontology and data standardization needs of DAIT-funded experimental scientists,
*identifying ontologies to be used in submitting data from ImmPort,
*identifying strategies for data retrieval, including strategies based on natural language processing.


The goals of Day 2 are:
== Wednesday, September 4, 2013 ==
*to introduce those new to ontology to the tools and methods involved in ontology development and use,
*to provide an overview of ontology resources of particular interest to the ImmPort / HIPC and related communities,
*to work with immunologists who have data which pose special problems for handling in a resource such as ImmPort, and to develop detailed ontology-based strategies to address these problems that are designed to be of lasting utility.


'''Draft Schedule'''
'''Schedule'''


<u>Wednesday, September 4, 2013</u>
:8:30 Registration and Continental Breakfast


8:30 Registration and Continental Breakfast
:9:00 Barry Smith (Buffalo): Overview of ImmPort Ontologies [http://ncor.buffalo.edu/2013/Immunology/Smith.pptx Slides]


9:00 What Ontology Can Bring the DAIT Research Community
:9:15 Jeff Wiser (Northrop Grumman): Discussion on the Role of Ontologies in ImmPort
:Overview by Barry Smith


10:30 Ontology, NLP and the Semantic Enhancement of Immunology Research Literature
:9:45 Atul Butte (Stanford / ImmPort): The Future of ImmPort [http://ncor.buffalo.edu/2013/Immunology/Butte.pdf Slides]
:Including presentation by Shai Shen-Orr (Technion Israel Institute of Technology)


12:00 Lunch
:10:00 Garry Nolan (Stanford): Goals for CyTOF


13:00 ImmPort Ontologies
:11:00 Break
:An overview of ontologies proposed by ImmPort for use across the immunology research community. For background see [http://ncorwiki.buffalo.edu/index.php/Immunology_Ontologies here]
*Anna Maria Masci: The Immunology Ontology
*Lindsay Cowell: The Infectious Disease Ontology


15:00 Flow Cytometry and CyTOF Data Using the Cell Ontology
:11:15 Alex Diehl (Buffalo): PRO and CL [http://ncor.buffalo.edu/2013/Immunology/Diehl.pptx Slides]
*Courtot/Brinkman: http://ontology.buffalo.edu/pro/CytometryOntologyFramework.pdf The Cytometry-Ontology Framework]
*PRO, CL and CyTOF


<u>Thursday, September 5, 2013</u>
:11:45 Alan Ruttenberg (Buffalo): The Ontology for Biomedical Investigations (OBI) [http://ncor.buffalo.edu/2013/Immunology/Ruttenberg.pdf Slides]


8:30 Continental Breakfast
:12:15 Lunch


9:00 An Introduction to Ontology for Immunology  
:13:00 Holden Maecker (Stanford):Flow Cytometry Standardization and the Problem of Cell Typing [http://ncor.buffalo.edu/2013/Immunology/Maecker.pdf Slides]


10:00 Immunology in the Gene Ontology (Alexander Diehl)
:14:00 Ryan Brinkman (Vancouver): [http://ontology.buffalo.edu/pro/CytometryOntologyFramework.pdf The Cytometry-Ontology Framework] [http://ncor.buffalo.edu/2013/Immunology/Lyoplate_CL%20mapping_29AUG2013%20(1).xlsx Supplementary data]


10:30 VDJServer (Lindsay Cowell)
:14:45 Melanie Courtot (Vancouver): Enabling Faster and More Accurate Analysis of Vaccine Adverse Event Reports with Ontology Support


11:00 Further Use Cases
:15:15 Break


12:00 Lunch
:15:30 Lindsay Cowell (Southwestern Medical Center): VDJ Repertoire and Ontology-Based Data Sharing [http://ncor.buffalo.edu/2013/Immunology/Cowell.pdf Slides] [http://ncor.buffalo.edu/2013/Immunology/Cowell1.pdf Slides 1] [http://ncor.buffalo.edu/2013/Immunology/Cowell2.pdf Slides 2]


13:00 Further Use Cases
== Thursday, September 5, 2013 ==


16:00 Close
'''Schedule'''


:8:30 Continental Breakfast


:9:00 Nikesh Kotecha (Stanford / Cytobank): Software Challenges for Cytometry [http://ncor.buffalo.edu/2013/Immunology/Kotecha.pdf Slides]


'''Participants''' (* = tentative)
:9:30 Yannick Pouliot, Alex Diehl, Chris Mungall: Symposium on the Cell Ontology (CL)
::Cell types, cell stages, cell populations and CL terms and definitions.


Lindsay Cowell (UT Southwestern, Dallas)
:10:30 Break
* *Melanie Courtot / Ryan Brinkman (Vancouver, BC)
Alexander Diehl (ImmPort / Buffalo)
* *Anna Maria Masci (Duke)
Alan Ruttenberg (ImmPort / Buffalo)
Shai Shen-Orr (ImmPort / Technion Institute)
Barry Smith (ImmPort / Buffalo)
* *Christian Stoeckert (Penn)


Very tentative:
:11:00 Alan Ruttenberg, Barry Smith: A Debate on Strategies for Use of Ontologies in ImmPort
* *James S. Cavenaugh (University of Rochester Medical Center)
* *Oliver Crespo (BD Biosciences, San Jose, CA)
* *Peter d'Eustachio (New York University)
* *Oliver He (University of Michigan)
* *Yu Lin (University of Michigan)
* *Darren Natale (Georgetown University)
* *Dave Parrish (Digital Infuzion)
* *Bjoern Peters (La Jolla Institute for Allergy and Immunology)
* *Veronica Shamovsky (NYU School of Medicine)
* *Cathy Wu (University of Delaware, Georgetown University)
* *Alex C. Yu (Seattle)


Plus participants from Stanford
:12:00 Lunch
 
:13:00 Open Discussion: Consequences for the Future of Immunological Science
::Topics to be addressed
::*The Cell Ontology as Canonical Ontology: The Case of OncoCL [http://ncor.buffalo.edu/2013/Immunology/Dolan.pdf Slides]
::*How do we create a Cell Stage / Cell State Ontology?
::*Do we need a Cell System (Immune Cell System, Cancer Cell System, (Intercellular, Stroma ...)
 
:15:00 Shai Shen-Orr (Tel Aviv): Ontology, NLP and the Semantic Enhancement of Immunology Research Literature
 
:16:30
 
'''Major Questions for Discussion'''
 
1. Evaluation of the cell type definitions proposed in [http://www.ncbi.nlm.nih.gov/pubmed/22343568 Maecker et al.] (if possible do this prior to the meeting)
 
2. What should be the framework by which we can represent cell populations identified through given sorts of assays in such a way that we can later promote them to cell types recognized in the CL?
 
3. How do we determine what is really a new cell type rather than either a refinement of an existing cell type generated by additional markers, or (2) a transient activation state of some known cell type?
*Subtasks:
:'''Ontological Background'''
::a. explain the difference between continuant and occurrent
::b. summarize how this difference is handled in other ontologies (especially GO)
::c. list a set of properties that distinguish a cell type (continuant) from a transient state type (occurrent)
:'''Metadata'''
:What metadata need to be captured in order to enable the downstream determination that a cell population identified by some assay is in fact either (a) a bona fide cell type that should be included in CL, or (b) a bona fide cell state type?
*Proposed:
:a. composition of the antigen panel
:b. antibodies used to probe each antigen (expressed as ImmPort Antibody Registry ID)
:c. the type of flow experiment: traditional, phosphoflow, CyTOF
:d. unique experiment ID
:e. species of the cells being probed (NCBI Taxonomy ID)
:f. type of sample (whole blood, PBCs)
:g. combination of markers that define a cell type according to the experimenter
:h. clinical status of subjects (affected, unaffected; vaccinated/unvaccinated)
:i. interventions (e.g., which arm of a trial the subject belongs to)
 
(At least in the short-run, it is anticipated that these data will be obtained from ImmPort's store of flow data.)
 
More ambitious questions for discussion if time allows:
 
3. Can we leverage CyTOF to develop a true step-by-step picture of hematopoiesis? This is a question for both ontology and the experimental approach.
 
4. What surface markers or internal proteins have reliable associations with biological processes, such that when we see a novel cell type or a variant of a known cell type we can predict the cell's function or (in other words the GO:Biological Processes it is capable of carrying out or participating in)? This question can obviously leverage existing GO annotations for particular proteins, some of which already have co-annotation with CL terms. But it can also lead to new terms for GO:Biological Processes and for CL cell types.
 
== '''Participants''' ==
 
* Sanchita Bhattacharya (ImmPort / Stanford)
* Ryan Brinkman (Vancouver, BC)
* Atul Butte (ImmPort / Stanford)
* Quan Chen (NIH / NIAID)
* Lindsay Cowell (UT Southwestern, Dallas)
* Melanie Courtot (Vancouver, BC)
* Alexander Diehl (ImmPort / Buffalo)
* Nikesh Kotecha (Stanford)
* Suzanna Lewis (Berkeley)
* Holden Maecker (Stanford)
* Chris Mungall (Berkeley)
* Garry Nolan (Stanford)
* Yannick Pouliot (ImmPort / Stanford)
* Alan Ruttenberg (ImmPort / Buffalo)
* Nikolay Samusik (Stanford)
* Ravi Shankar (ImmPort / Stanford)
* Shai Shen-Orr (ImmPort / Technion Institute)
* Barry Smith (ImmPort / Buffalo)
* Nicole Vassilesky (OHSU, Oregon)
* Jeff Wiser (ImmPort / Northrop Grumman)
* Ashley Xia (NIH / NIAID)
 
Plus further participants from Stanford area.

Latest revision as of 20:32, 6 September 2013

Where: Paul Berg Hall A #230, Li Ka Shing Center for Learning and Knowledge, 291 Campus Drive West, Stanford School of Medicine, Stanford, CA 94305.

When: September 4-5, 2013

Audience

  • Day 1 is intended for all those engaged in information-driven immunology research who have an interest in the work of ImmPort and/or in ontology and data standardization
  • Day 2 (by invitation only) is intended primarily for those interested in CyTOF and related issues of data management in immunological science.

Background resources

  • An overview of ontologies proposed by ImmPort for use across the immunology research community is provided here

If you are interested in attending please contact Barry Smith as soon as possible.

Wednesday, September 4, 2013

Schedule

8:30 Registration and Continental Breakfast
9:00 Barry Smith (Buffalo): Overview of ImmPort Ontologies Slides
9:15 Jeff Wiser (Northrop Grumman): Discussion on the Role of Ontologies in ImmPort
9:45 Atul Butte (Stanford / ImmPort): The Future of ImmPort Slides
10:00 Garry Nolan (Stanford): Goals for CyTOF
11:00 Break
11:15 Alex Diehl (Buffalo): PRO and CL Slides
11:45 Alan Ruttenberg (Buffalo): The Ontology for Biomedical Investigations (OBI) Slides
12:15 Lunch
13:00 Holden Maecker (Stanford):Flow Cytometry Standardization and the Problem of Cell Typing Slides
14:00 Ryan Brinkman (Vancouver): The Cytometry-Ontology Framework Supplementary data
14:45 Melanie Courtot (Vancouver): Enabling Faster and More Accurate Analysis of Vaccine Adverse Event Reports with Ontology Support
15:15 Break
15:30 Lindsay Cowell (Southwestern Medical Center): VDJ Repertoire and Ontology-Based Data Sharing Slides Slides 1 Slides 2

Thursday, September 5, 2013

Schedule

8:30 Continental Breakfast
9:00 Nikesh Kotecha (Stanford / Cytobank): Software Challenges for Cytometry Slides
9:30 Yannick Pouliot, Alex Diehl, Chris Mungall: Symposium on the Cell Ontology (CL)
Cell types, cell stages, cell populations and CL terms and definitions.
10:30 Break
11:00 Alan Ruttenberg, Barry Smith: A Debate on Strategies for Use of Ontologies in ImmPort
12:00 Lunch
13:00 Open Discussion: Consequences for the Future of Immunological Science
Topics to be addressed
  • The Cell Ontology as Canonical Ontology: The Case of OncoCL Slides
  • How do we create a Cell Stage / Cell State Ontology?
  • Do we need a Cell System (Immune Cell System, Cancer Cell System, (Intercellular, Stroma ...)
15:00 Shai Shen-Orr (Tel Aviv): Ontology, NLP and the Semantic Enhancement of Immunology Research Literature
16:30

Major Questions for Discussion

1. Evaluation of the cell type definitions proposed in Maecker et al. (if possible do this prior to the meeting)

2. What should be the framework by which we can represent cell populations identified through given sorts of assays in such a way that we can later promote them to cell types recognized in the CL?

3. How do we determine what is really a new cell type rather than either a refinement of an existing cell type generated by additional markers, or (2) a transient activation state of some known cell type?

  • Subtasks:
Ontological Background
a. explain the difference between continuant and occurrent
b. summarize how this difference is handled in other ontologies (especially GO)
c. list a set of properties that distinguish a cell type (continuant) from a transient state type (occurrent)
Metadata
What metadata need to be captured in order to enable the downstream determination that a cell population identified by some assay is in fact either (a) a bona fide cell type that should be included in CL, or (b) a bona fide cell state type?
  • Proposed:
a. composition of the antigen panel
b. antibodies used to probe each antigen (expressed as ImmPort Antibody Registry ID)
c. the type of flow experiment: traditional, phosphoflow, CyTOF
d. unique experiment ID
e. species of the cells being probed (NCBI Taxonomy ID)
f. type of sample (whole blood, PBCs)
g. combination of markers that define a cell type according to the experimenter
h. clinical status of subjects (affected, unaffected; vaccinated/unvaccinated)
i. interventions (e.g., which arm of a trial the subject belongs to)

(At least in the short-run, it is anticipated that these data will be obtained from ImmPort's store of flow data.)

More ambitious questions for discussion if time allows:

3. Can we leverage CyTOF to develop a true step-by-step picture of hematopoiesis? This is a question for both ontology and the experimental approach.

4. What surface markers or internal proteins have reliable associations with biological processes, such that when we see a novel cell type or a variant of a known cell type we can predict the cell's function or (in other words the GO:Biological Processes it is capable of carrying out or participating in)? This question can obviously leverage existing GO annotations for particular proteins, some of which already have co-annotation with CL terms. But it can also lead to new terms for GO:Biological Processes and for CL cell types.

Participants

  • Sanchita Bhattacharya (ImmPort / Stanford)
  • Ryan Brinkman (Vancouver, BC)
  • Atul Butte (ImmPort / Stanford)
  • Quan Chen (NIH / NIAID)
  • Lindsay Cowell (UT Southwestern, Dallas)
  • Melanie Courtot (Vancouver, BC)
  • Alexander Diehl (ImmPort / Buffalo)
  • Nikesh Kotecha (Stanford)
  • Suzanna Lewis (Berkeley)
  • Holden Maecker (Stanford)
  • Chris Mungall (Berkeley)
  • Garry Nolan (Stanford)
  • Yannick Pouliot (ImmPort / Stanford)
  • Alan Ruttenberg (ImmPort / Buffalo)
  • Nikolay Samusik (Stanford)
  • Ravi Shankar (ImmPort / Stanford)
  • Shai Shen-Orr (ImmPort / Technion Institute)
  • Barry Smith (ImmPort / Buffalo)
  • Nicole Vassilesky (OHSU, Oregon)
  • Jeff Wiser (ImmPort / Northrop Grumman)
  • Ashley Xia (NIH / NIAID)

Plus further participants from Stanford area.