# Presentation: 863987

## Molecular Analysis of Cancer

**(*****Director’s Challenge)***

_**Informatics Support**_** for NCI Initiatives:**
- Director’s Challenge
- Mouse Models in Cancer
- SPORES
- & other intra- and extramural research groups
_**Data Base and Analysis/Visualization Tools**_ for
- Gene Expression Data
- CGH data (BAC and cDNA arrays)
- SAGE Data
_**Future Focus:**_
- Support for additional platforms.
- Development of visualization tools to facilitate correlation and integration of these data.

## Gene Expression Analysis Workbench

***Gene Expression Analysis Workbench***
*First Genetic Trust*
*Open source, client-side Java application*

## Comparative

***genomic***
***hybridization***
***(CGH)***

**Competitive hybridization  of DNAs labeled with green and red fluorescent colors**
**Measurement of green-to-red ratio**
**Increased green color --> amplifications**
**Increased red color --> deletions**

**Kallioniemi et al., Science 1992**

## CGH on cDNA Microarrays: Gene-level Resolution

***CGH on cDNA Microarrays: Gene-level Resolution***

**Notes:**
The first is resolution:

In chromosomal CGH,  the hybridization target is a normal metaphase chromosomes. Therefore the resolution of this technique is limited by that of the cyogenetic map to approximately -20Mb

In contrast, CGH microarray uses cDNA targets. Each gene is  represented by a clone on the microarray and so has a copy number ratio associated with it. This allows us to have as good as single gene resolution

## CGH Viewer and Data Mining Tool

***CGH Viewer and Data Mining Tool***
*Research Triangle Institute*
*Open source, web-based Java application*

-  Significant deviation from normal
-  >2X increases or decreases
-  High level increase or decrease in a few tumors

- Genome location

- Frequency

**UCSF Comprehensive Cancer Center**

## Slide 6

## Data Integration:

**CGH Array **
**FGFR2 (G/R=16)**

**cDNA Array **
**FGFR2 (G/R=41)**

***Data Integration:***
**Copy Number** (CGH arrays)
**Expression**
- Spotted, Affy,  SAGE
**Pathways**
- Chromosomal Rearrangements (SKY)
- CGH
- Mutations
- Methylation status
- Protein data

## SAIC-team:

***SAIC-team:***
- GEDP, XpressionWay, Integration of Open Source Tools...

## Gene Expression Data Portal (GEDP)

- The Gene Expression Data Portal (GEDP) allows users to submit, search, and analyze microarray    experiments            (Affy, Spotted Arrays, and Other as of 1.1.2)
- The microarray    database was       designed based on industry standards (MAGEML)

## Experiment Submission

- Users can submit information common to all microarrays in experimental studies

## Existing Data Sets

- NCI 60 – Microarray Data, Spotted Array Platform, 60 Arrays from NCI
- CGAP SAGE – 112 Libraries from CGAP
- Donna Albertson – 25 Arrays of CGH Data from UCSF
- Pat Brown – 10 Arrays of CGH Data from Stanford
- NCBI Affy – 116 Arrays from 6 Experiments
- NCBI SAGE – 23 Libraries
- Jeff Green and John Weinstein – NCI
- George Michalopoulos, Michael Becich –               Univ. of Pittsburgh Medical School

## Expecting More Data Sets after 1.1.2 Deployed

- Ann Arbor experiments from Michigan
- RTPCR and Filter Array data sets
- Experiments in unknown format will be uploaded using new “Other” feature.

## Experiment Search

- Researchers can search for experiments by investigator, tissue type, species, and array platform

## Search Results

- Experiment details can be obtained by selecting an experiment from the Search Results screen
- Data files associated with selected experiments can be downloaded
- Data can be downloaded in MAGEML format
- Data sets can be analyzed and retrieved

## Data Set Analysis

- Researchers select the array(s) to analyze
- Researchers can provide data set pre-processing options
- Options include spot filtering and data normalization methods
- Data is processed and normalized leveraging the ‘R’ statistical package for gene expression

## Pathways in Array

- Researchers can retrieve a list of pathways associated with the selected data set
- Researchers can view each pathway, select the genes on the chip, and view expressed genes

**Powered **
**by **
**caBIO!**

## Pathway Summaries

- Researchers can view the level of expression of target genes affiliated with selected experiments
- Researchers can also view information about each gene
- Information includes sequence accession #’s, links to data sources (Unigene, etc.), libraries/tissues, protein similarities, DAS annotations, etc.

**Powered **
**by **
**caBIO!**

## GEDP Release 1.1.2

- Planned Deployment:  3/2003
- Testing starts 2/27
- Enhanced the file upload Applet to accommodate all file types and added additional file validation checks
- Added support for Cy3/Cy5 data
- Added links to PubMed

## Enhanced File Upload Applet

**Progress Bar**

**File Filter**

## Support for Cy3/Cy5

## PubMed Links

## GEDP Future Features

- Support additional experiment file types including Affy .cel file, CGH data, and Stanford data sets
- Provide MAGE-OM APIs supporting MAGEML input/output
- New User Interface
- Common Vocabulary Interface
- Analysis Tool Enhancements
- Integrate with TIGR tools
- Leverage the BioConductor R modules
- XpressionWay Enhancements
- Support interface between FGT and RTI analysis tools

## Affy Cel File Persistence

- Investigating parsing/persistence of Affy cel files
- Issues being investigated
- Need to parse both ascii format and binary format .cel files.
- Need to store in format that allows efficient feature lookup.

## MAGE-OM Approach

- Provides programmatic access via RMI interfaces to data in GEDP database
- Utilizes Database views to access GEDP data.  Views are designed to “abstract away” discrepencies between GEDP schema and MAGE schema.

## GEDP/MAGE-OM Architecture

**GEDP Application Server **

**MAGE-OM Web Application Server**

**GEDP   Database **

**MAGE  Database **

**MAGE-OM RMI Server**

**MAGE View**

**Client Browser**

*Retrieve Request*

*Retrieve/Submit Request*

**Client Application**

**R – Stats   Server**

**caBIO MAGE Package**

**caBIO**

*Genes, Pathways*

*R-Caller*

*Raw/Processed Data       MAGEML*

*MicroArray Data*

## New User Interface

- Changes to look and feel
- Focus on “walking user through experiment submission”.
- Sample pages follow

## Home Page: Step 1

## Download Template

## Home Page: Step 2

## Home Page: Step 3

## Future Analysis Tools

- Enhancements to ExpressionWays tool
- Ability to view pathways of ad-hoc experiments given a set of genes and features in an uploaded spreadsheet.
- Show number of up/down expressed genes in the pathway list for each pathway to assist users in determining which pathways are important to view.
- Working to support FGT and RTI in creation of additional analysis tools.
- Tools will be maintained by GEDP development team after initial delivery.