Oncomine Database
www.oncomine.org
Lauren Smalls-Mantey
Georgia Institute of Technology
June 19, 2006
Note: This presentation contains animation
What is Oncomine?
• A unifying bioinformatic resource of analyzed
cancer transcriptome data.
• A resource to help clinicians to view others
research data to aide in the discovery of gene
interaction.
Oncomine Database
Data Pipeline
• Includes studies from
published literature and other
databases.
• Screens microarray data only
to include those studies that
meet the oncomine standards
(clinically important).
Annotation Data Warehouse
• Links 14 databases
• Includes automatic updates
from the database sites.
Log-In Screen
This is the first screen seen after loging in to www.oncomine.org
Search by: Gene Name
Gene Symbol
Unigene ID
Entrez Gene ID
Affy Probeset #
Image Clone ID
Accession #
Search by: Keyword
Author_Tissue
Tissue type
Cancer Type
Clinical/Pathological
Parameters
Search for Breast Cancer
Author_type of cancer
Description of Cancer
Class: # of patients in study
Measured: # of reporters analyzed
Up: # of Over expressed genes
Down: # of Under expressed genes
Diff: # of Differentially expressed genes
1
2
1.
Clicking on the
author gives a
description of the
study analyzed
and a copy of the
paper
2.
A thesaurus is
attached to many
of the words, which
creates a standard
language for all
users.
Oncomine Database
Automated Data Analysis
• Performs logical differential
expression analyses, cluster
analyses, and concept
analyses.
• Permits the use of other
hypothesis not explored in the
paper
Sample Facts Standardization
• Standardizes and curates
sample information
Simple Analysis of Data
To perform a simple analysis on the data in the published work simply click on the highlighted regions.
Heat Map
Gene List
Box plot of gene
Analysis
Modules
Advance Analysis
By clicking on the highlighted icon, advanced analysis (AA) of the
data can be computed. This encompasses all of the analysis
modules.
Advanced Analysis
AA: Differential Expression
Clicking on
any gene will
give the
Gene
Annotation
Box plots of each
gene are available
by clicking on the
icon.
Enrichment
This module provides links to the databases in the data warehouse.
Below is a list of some of the advanced analysis it provides:
GO Cellular Component- Gene Ontology Database (gene product descriptions)
KEGG Pathway- KEGG (gene-gene interaction)
Literature-define Concepts- Pubmed
Interpro- Interpro (protein database)
Chromosome Subregion- NCBI Mapview (organism genome search)
Oncomine Gene Expression Signatures- Oncomine (where gene is found in other
publications)
Chromosome Arm- NCBI Mapview (organism genome search)
Conserver Promoter Motif- Pubmed (publications where motif can be found)
picTar predicted miRNA target genes – picTar (miRNA constructs)
Enrichment Module
Interaction Networks
Clicking on this button
provides a gene
interaction pathway,
which includes the
genes listed.
Co-Expression
Co expression plots of the two genes are also available.
Meta Analysis
Meta analysis between different experiments allows for validation and assessment of
accurate results. It only compares the statistical measurements because preparation
methods are different between experiments. It also attempts to eliminate artifacts and cross
hybridization.
1
At the first results page click the experiments to be compared.
Meta Analysis Cont…
2
3
Click the Advanced Analysis at the bottom of the screen
The screen that
appears is similar to
the results page
At the bottom
select the
expression type
and any filters
Meta Analysis Cont…
Click on Metamap
or Gene List to
display module
4
Box plots
are also
available
Using Oncomine
Advantages
• Web based program
• Meta analysis between different experiments
• Easy to use interface across the spectrum of
researchers
• Bridges the gap between clinicians (can use
when tumor samples are low due to wide
variety of samples on the database).
• High level analysis
• All analyzed data standardized
• Co-Expression Analysis
Identifies genes that are similarly
expressed across several tissue samples
within various experiments
Disadvantages
• Only includes cancer specific data
• Must go through external sites for raw
data therefore raw data is not in a
standardized format.
• Need login access (free for academic
not free for civilians)
• The link to the databases does not take
you directly to the page for the specific
gene. The user must search the
database themselves.
Help is no problem
At the upper right of
each module is a
‘question mark.’ This
will take you to a
help page for the
module.
Data Pipeline Data Bases:
• Gene Expression Omnibus (GEO)
• Stanford Microarray Database (SMD)
• Array Express
Gene Annotation Data Warehouse:
From:
www.oncomine.org