#### ICR Workspace Teleconference 

May 28, 2008; 2:00 -- 4:00 pm ET\
Moderator: Elaine Freund

#### 

#### Executive Summary

-   caLIMs (cancer Laboratory Information Management System) -- *Jenny
    Kelley, Bioinformatics Specialist in the Laboratory of Population
    Genetics (LPG) Bioinformatics Core*

-   CPAS (Computational Portal and Analysis System )--*, Denny Chan*,
    *CBITT Proteomics Projects*

-   Cancer Gene Index -- *Pat Blake, CEO of Sophic Systems Alliance,
    Inc.*

#### 

#### Key Outcomes and Decisions

#### 

#### Action Items

+----------------+--------------------------------------+-------------+
| ##             | #### Description                     | ##          |
| ## Assigned To |                                      | ## Due Date |
+----------------+--------------------------------------+-------------+
| #### All       | #### Provide feedback to Pat Blake   | ####        |
|                |  and Juli Klemm on Cancer Gene Index |             |
+----------------+--------------------------------------+-------------+

#### 

#### 

#### Meeting Notes

ANNOUNCEMENTS

v4.1 of caBIO 4.1 released and contains:

-   Data Refresh

-   Cancer Gene index data

-   Some model changes (mostly additions of subclasses)

<http://cabioapi.nci.nih.gov/cabio41>

Nature Reviews: Cancer published an article entitled "The Mouse Tumor
Biology Database" which describes work done at Jackson Lab and is a
content source for caBIG data repositories.

The Life Sciences Distribution tool demos are available at:

[[https://cabig.nci.nih.gov/tools/toolsuite_view#LSD]{.underline}](https://cabig.nci.nih.gov/tools/toolsuite_view#LSD)

#### 

#### 

#### PRESENTATIONS

[caLIMs (cancer Laboratory Information Management System)]{.underline}
-- Jenny Kelley, Bioinformatics Specialist in the Laboratory of
Population Genetics (LPG) Bioinformatics Core

<https://gforge.nci.nih.gov/frs/download.php/4080/caLIMS2_ICR_28May08.ppt>

#### caLIMS is a 2^nd^ generation LIM system designed and developed using caBIG principles and best practices. The software will be caBIG compliant out of the gate and is designed to fills gap between repositories and analytical tools in the grid.

#### Example work flow with ICR tools: Clinical study or caTissue repository feeds information into caLIMs to data repositories or tools such as caArray or caGWAS and data analysis tools like geWorkbench and GenePattern. Analysis results and annotations can be returned back to various repositories via the LIMS.

#### 

#### Use case -- 80 samples are tracked, Affy assays performed and results are loaded into caArray. With time points, dilutions and repetitions, there are 3000 files and associated meta data.

#### Doesn't require large IT resources or have a high cost to implement and use.

#### caBIG compatible on release, public contributions are welcome, there are rapid development cycles, there are a large number of sources for feedback.

#### caLIMs has a modular design. Modules: Admin, Inventory, Workflow, Analysis, Report

#### Models were shown and reuse was (such as from caTissue) noted. This should reduce integration issues. 

#### Plan to use Taverna for workflow management.In Workflow -- there is the concept of a template project -- to tightly control some experiments. They can be modified when pulled into a new project.

#### There are no SQL queries required, caLIMs uses Hibernate.

#### Can view and retrieve code and documentation via GForge.

#### Have a monthly consortium meeting the 4^th^ Monday of the month at 1.

#### Can sign up for listserv and other meetings are open.

#### 

#### Questions:

#### Will this all be automated or will some manual transfer be required? caLIMs is still in dev, but yes, the plan is for it to be fully automated.

#### If components of a workflow are in various places on the Grid, does caLIMs handle information securely? The grid security systems will be used and fine grained tracking within caLIMs is possible. Data is only available to those with permission -- files are uploaded as private and the user would have to change it to public.

#### How accessible is this for beta use? CBIIT and LPG each host an instance -- there are many others listed as ready to be early adopters.

#### Will caLIMs be able to interface with caExchange? The team wants to pursue this and could do something there. 

#### 

#### 

#### 

[CPAS (Computational Portal and Analysis System )]{.underline} -- *Denny
Chan*, *CBITT Proteomics Projects*

#### <https://gforge.nci.nih.gov/frs/download.php/4081/ICR_200805.ppt>

#### 

#### CPAS -- is a portal and Mass Spectrometry repository and analysis system hosted by NCICBIIT.

#### It has a modular architecture and is easily extensible. Modules can be added and integrated to core system.

#### There is an extensive repository of 10M peptides organized with a folder format.

#### Blast searching is used so query performance is satisfactory. You can view/filter by peptides, spectra, sequence and other parameters.

#### 

#### CPAS MART -- query service built upon BioMART. It allows you to decide what data you want to expose and how you want to view the data (eliminates some CPAS constraints). It has tools to configure and customize a CPAS-MART schema. It creates a new schema and so doesn't impact the original CPAS schema. You can view results in a variety of formats and there is e-mail notification for queries that take a long time to execute.

#### 

#### CPAS-Grid (CPAS grid enabled) \-- CPAS-Grid has caBIG silver level compliance. There is an API to access objects, etc. and you can use the discovery service to find what and where services are available and use the APIs or the caGrid Portal to access and retrieve CPAS data. 

#### 

#### There was a live demo of each of the components.

#### 

#### Questions:

#### Can you use caDSR standards? Is there a plan to re-use CDEs and standards for interoperability? There are join points with existing ICR tools and services \-\--

#### This would require another round of model development. FHRCC is the developer, so it is not clear.

#### Is CPAS-MART discovery and use complicated by the ability to change the schema? Each CPAS-MART would have to be submitted for it's own compliance review.

#### 

#### 

#### 

[Cancer Gene Index]{.underline} -- *Pat Blake, CEO of Sophic Systems
Alliance, Inc.*

#### 

<https://gforge.nci.nih.gov/frs/download.php/4082/Cancer_Gene_Index_ICR_PRESENTATION_052808_final.ppt>

<https://gforge.nci.nih.gov/frs/download.php/4083/CancerGeneIndex_Vocabulary_compound_condensed210508.pdf>

#### [**https://gforge.nci.nih.gov/frs/download.php/4084/CancerGeneIndex_Vocabulary_disease_condended210508.pdf**](https://gforge.nci.nih.gov/frs/download.php/4084/CancerGeneIndex_Vocabulary_disease_condended210508.pdf)

#### 

#### Cancer Gene Index uses automated and manual text mining to identify all genes related to cancer. Sentences are automatically extracted and then read and manually annotated by curators for things such as evidence code, role, organism, etc.

#### 

#### Pilot was initiated in 2004. There were additional option years and including work on the Atlas Project. The project is now being extended.

#### 

#### There are 6610 identified cancer genes and there are 1952 left to annotate.

#### 310 high freq count genes (p53, BRCA) \>1000 sentences

#### 1652 \<1000 sentences

#### The scope of the current project is to curate 250K gene-disease and 250K gene-compound sentences.

#### 

#### Using the 80/20 rule, 80% can be annotated with 10 sentences (or less) per relationship but 20% have 65K sentences. The question is how to prioritize what to curate.

#### 

#### Pat showed disease categories -- and the terms in them. Sentences were clustered and gave counts that have all, 3, 2, 1 terms. 

#### 

#### Plan on using date to identify publications

#### Pat and Juli asked for:

#### A review of terms -- there are 2 sheets for comments

#### Is strategy logical? Do you have other ideas to improve deliverable?

#### How to choose sentences to manually annotate?

#### 

#### 

#### Questions: 

#### Ranking by science citation index? Journal impact factor? Discussion followed.

#### Why the high \# of high frequency genes (HFG)? There is no rigorous definition on true cancer genes. The criteria is if a name and disease name occur in sentence and there is a clear disease type association, it is counted.

#### Comment - 7K genes out of 25K in genome - so all genes involved in cancer. 

#### Suggestion - Break genes out into other or sub- groups.

####  Pathway

####  Direct cause with mutation

#### Why is 1K sentences used as the criteria for HFG vs not? A bit arbitrary -- but did use statistics on sentence distribution and there was a natural break point.

#### How does CGI compare to OMIM for cancer genes? Is it a full subset? There may be a few discrepancies but OMIM had been the standard and there was a very good comparison.

#### 

#### 

#### 

#### Next Meeting:

#### Wednesday June 11, 2008

#### 2:00 -- 4:00 pm ET

Number: 800-593-0616

Passcode: 2927756

Centra Meeting:
[[http://ncicb.centra.com/]{.underline}](http://ncicb.centra.com/)

#### Event ID: ICR_WS

#### 

#### 

#### Attendees

  ----------------------------------- -----------------------------------
  Li Kramer                           Booz Allen Hamilton

  Elaine Freund                       3^rd^ Millennium

  Wei Wang                            Univ. of North Carolina

  Uma Chandran                        Univ. of Pittsburgh

  Tom Boal                            

  Terry Braun                         Univ. of Iowa

  Ted Liefeld                         Broad

  Sue Pan                             NCI

  Sashi                               

  Samira Guccione                     

  Sal Mungal                          Duke Univ.

  Rohit Pappu                         

  Robert Freimuth                     Mayo Clinic

  Pankaj                              Duke Univ.

  Mukesh Sharma                       Wash Univ.

  Mary McAdams                        

  Martin Morgan                       Fred Hutch

  Liming Yang                         NCI

  Leonard McMillan                    Univ. of North Carolina

  Lalitha Viswanath                   NCI

  Kiran Keshav                        Columbia Univ

  Grace Stafford                      The Jackson Laboratory

  Donna Messersmith                   SAIC

  Deven                               

  Denny Chan                          NCI

  David Steffen                       Baylor

  David Paik                          Stanford

  Charlie                             

  Benjamin Powers                     

  Baris Suzek                         Georgetown

  Juli Klemm                          NCI

  Mervi                               NCI

  Jenny Kelley                        NCI

  Bart Brown                          

  Klaus Heumann                       Biomax

  Pat Blake                           Sophic Systems Alliance
  ----------------------------------- -----------------------------------

#### 

####