Genopolis Microarray DB a Progress Report
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Transcript of Genopolis Microarray DB a Progress Report
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Genopolis Microarray DBGenopolis Microarray DBa Progress Reporta Progress Report
Genopolis Microarray DBGenopolis Microarray DBa Progress Reporta Progress Report
Marco Brandizi<[email protected]>
Dec 12, 2005
Dottorato in InformaticaXIX Ciclo
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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DNA
gene
mRNA
protein
Genes Machine
Cell/Life
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Microarray Data, conceptual model
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Microarray Data Management Issues
Exp. data vs. seq. data:
Context dependent (living system, exp. Conditions)
Lack of standard unit of measure
Several normalizations methods
Multiple platforms and methods
No standard for data annotation
Vocabularies and terminology coherence
Details about: experiment, source, protocols, exp.
conditions
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Microarrays Data Management Issues / 2
Evidences about data quality
What to store?
Raw Images
Computed values
Normalized values
How to find data
Complex vocabularies aware systems (ontologies)
Data mining and exp. comparison tools
Data access control
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MIAME Experiment Modeling
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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GCA FeaturesCurated experimental design representation
MIAME-compliant, (although with simplified model)
Use of controlled vocabularies
Experiment checking/publishing, with supervision
Targeted to Affymetrix platform
Chip description is simple, imported from NETAffx
Single channel technology
Access control
Users are grouped into groups and access roles
Experiments belong to user groups
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GCA FeaturesData Retrieval and visualization
Gene browser, a graphical visualization interface, based on the
matrix model
Search & Save data
Current content:
A set of time-courses about DCs stimulated with different stimuli
Implementation & Deployment
LAMP application (Linux + Apache + MySQL + PHP)
Model Viewer Controller as much as possible:
Business objects layer
Presentation widgets (DAO-lib)
Other application control layers
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GCA Features
Shortly:
A Gene Expression database software, focused
on Affymetrix technology, useful as a facility for a
distributed community of users
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GCA Data Model
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GCA Data Model
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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GCA Login
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GCA Editing
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GCA Experiment Checking
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GCA Import of chip annotations
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GCA CVs and protocols
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GCA CVs and protocols
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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GCA Gene Browser
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GCA Gene Browser
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GCA Gene Browser
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GCA Gene Browser
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GCA Gene Browser
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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GCA Access Management
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Bicocca Besta
Granucci
ADMIN
NormanTiranti
Andrea
Brandizi
Experiment 123
Ottavio
User PermissionsBrandizi, Andrea AllGranucci ReadNorman Read, WriteTiranti All (except admin)Ottavio None
User PermissionsBrandizi, Andrea AllGranucci ReadNorman Read, WriteTiranti All (except admin)Ottavio None
All but admin
All rights
R, W, -publish
Read only
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Access managementAccess managementAccess managementBased on a core library
Recent developments (security lib)
Code has been changed so that it uses security lib
All the code that interacts with user has been wrapped with
access management controls
Even malicious access attempts has been considered:
Handy writing of an URL
Handy request of an uploaded file (to be completed)
Does it work?
Yes, pretty sure
But more testing is needed
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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Search and Save
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Search and Save
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Search and Save
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Search and Save
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Search and Save
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Search and Save
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Search and Save
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Search and Save
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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MAGE ExportWill allow to export a GCA experiment to MAGE/Array Express
A collaboration with EBI
in the context of u-GENE
So far:
Schema of GCA->MAGE
(in AE compatible form)
Basic code fragments
(Business objects in Java)
Still to do
Full code
Mappings with MGED-Ontology
Tests with AE
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MAGE Export
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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GCA on cluster architectureThree machines, the minimum to have a cluster
Master (Xeon 3.2 Ghz, 2Gb RAM)
+ Master Clone that ensures high availability
computation node computers
(P4 3 Ghz, 512Mb)
1Tb of SCSI disk, shared via NFS
Based on:
Debian (Linux)
Linux Virtual Server
(Load Balancer)
Hearthbeat (High availability)
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GCA on cluster architecture
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GCA on cluster architectureCode needs slight changes:
PHP side and sessions:
Objects that are saved on session need to be reloaded properly
See:
http://it2.php.net/manual/en/language.oop.magic-functions.php#14473
__wakeup() is already used
__sleep() with proper return value is to be implemented
MySQL side:
The stable DB:
We need to specify the type of DB access: Read Only Mode vs.
Read/Write mode
RO access uses local copy of DB
RW access uses master copy
The temporary DB:
Only master copy exists (3307 port, current deployment)
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GCA on cluster architecturePossible other uses of cluster
Heavy computations (normalizations)
Integration with R (Grad. Thesis of L. Vanotti, Grad. Th. of M.
Sesana)
Other Integrations with R (AMDA)
Other related services
Knowledge management app.
Groupware Integration (DC-Thera)
Cytoscape Integration (DC-Thera)
Service mgmt. app.
R computations
BUT it has been designed for GCA
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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The mA Experiments Cycle
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“Closing the loop”
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What we need to model
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What we need to model
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What we need to model
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How to model: Semantic Web Technologies“The Semantic Web is an extension of the current web in whichinformation is given well-defined meaning, better enabling computersand people to work in cooperation.”
Tim Berners-Lee, James Hendler, Ora Lassila, The Semantic Web, Scientific American, May 2001
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Microarrays Annotation Ontology
Microarray entities
Annotation entities
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Microarrays Annotation OntologyAnnotation (source, target, child, parent, rank)
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Microarrays Annotation Ontology
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Microarrays Annotation Ontology
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Examples of useAnnotating a saved search
Comments and answer to comments
Originating operations (import, intersection, merge...)
Which user is working on this data set
Why the data set is being saved
Functional family
I'm studying IL2
I'm studying Shistosomia
disease
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Examples of use: AMDA
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Examples of use: AMDARepresentation an AMDA report in a structured form
DEGs and genes clusters
This is a DEG set, computed by AMDA (PAM method ) on samples
s1, s2, s3
Correlation between chips (storing values and links to
chip pairs)
Functional annotations of genes, by means of KEGG
(with reporting of significance)
Import of analysis annotations on GCA
Presenting analysis annotation together with data sets
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OutlineIntroduction
GCA Application
Main features
Demo
Demo/Gene Browser
Recent added features
Access control
Search & Save
Ongoing and future
MAGE Export
Migration on cluster
Management of knowledge about Higher Level Analysis
Other possible developments
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GCA: other possible developmentsTemplates for experiment insertion
Advanced CVs (taxonomies, mapping to MGED-Ontology)
Knowledge management features (with or without annotation
ontology)
e-Groupware and links between eGroupware
forums/documents and GCA experiments/data sets
Integration with AMDA (with or without annotation ontology)
Export of API, via Web Services Technology
Integration with Taverna or Cytoscape
Connections with pathway databases (ex.: by means of
Pathway processor)