microrray data standardisation
Download
Skip this Video
Download Presentation
Microrray Data Standardisation

Loading in 2 Seconds...

play fullscreen
1 / 32

Microrray Data Standardisation - PowerPoint PPT Presentation


  • 85 Views
  • Uploaded on

Microrray Data Standardisation. Microarray Gene Expression Database group -- MGED December, 2000. Public data repositories for microarray data.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Microrray Data Standardisation' - lemuel


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
microrray data standardisation

Microrray Data Standardisation

Microarray Gene Expression Database group -- MGED

December, 2000

public data repositories for microarray data
Public data repositories for microarray data

There is a growing consensus in the life science community for a need for public repositories of gene expression data analogous to DDBJ/EMBL/GenBank for sequences

some of the reasons
Some of the reasons:
  • Gradually building up gene expression profiles for various organisms, tissues, cell types, developmental stages, various states, under influence of various compounds
  • Through links to other genomics databases builds up systematic knowledge about gene functions and networks
  • Comparison of profiles, access and analysis of data by third parties
  • Cross validation of results and platforms - quality control
systematic gene expression profiling initiatives in public domain
Systematic gene expression profiling initiatives in public domain

The International Life Science Institute (ILSI) is coordinating a program undertaken by ~25 pharmaceutical and food companies to generate toxicity related gene expression data under defined experimental conditions

  • evaluate gene expression profiles in standardised test systems following exposure to toxicants
  • relate changes in gene expression to other measures of toxicity
microarray data handling and analysis a major bottleneck calculations by jerry lanfear
Microarray data handling and analysis - a major bottleneck (Calculations by Jerry Lanfear)
  • Experiments:
    • 100 000 genes in human
    • 320 cell types
    • 2000 compounds
    • 3 time points
    • 2 concentrations
    • 2 replicates
  • Data
    • 8 x 1011 data-points
    • 1 x 1015 = 1 petaB of data
expression data repository projects
Expression data repository projects
  • Public repositories in making:
    • GEO - NCBI
    • GeneX - NCGR
    • ArrayExpress - EBI
  • In-house databases - Stanford, MIT, University of Pennsylvania,
  • Organism specific databases: Mouse in Jackson
  • Proprietary databases - Gene Logic, NCI
difficulties
Difficulties
  • Raw data are images
  • What is needed for higher level analysis and mining is gene expression matrix (genes/samples/gene expression levels)
    • lack of standard measurement units for gene expression
    • lack of standards for sample annoation
raw data images
Raw data - images

Treated sample labeled red (Cy5)

Control data labeled green (Cy3)

Competitive hybridization onto chip

Red dot - gene overexpressed in treated sample

Green dot - gene underexpressed in treated sample

Yellow - equally expressed

Intensity - “absolute” level

red/green - ratio of expression

2 - 2x overexpressed

0.5 - 2x underexpressed

log2( red/green ) - “log ratio”

1 2x overexpressed

-1 2x underexpressed

cDNA plotted microarray

Stanford university (Yeast,1997)

gene expression matrix
Gene expression matrix

Samples

Genes

Gene expression levels

gene expression levels
Gene expression levels
  • What we would like to have
    • gene expression levels expressed in some standard units (e.g. molecules per cell)
    • reliability measure associated with each value (e.g. standard deviation)
  • What we do have
    • each experiment using different units
    • no reliability information
measurement units
Measurement units
  • In perspective:
    • standard controls for experiments (on chips and in the samples)
    • replicate measurements
  • Temporary solution:
    • storing intermediate analysis results (including the images) and annotations of how they were obtained - i.e., the evidence
comparing expression data problem 2
Comparing expression data - problem 2
  • How gene names relate in different data matrices?
  • How samples relate in different data matrices?
sample annotation
Sample annotation
  • Gene expression data have any meaning only in the context of what are the experimental conditions of the target system
  • Controlled vocabularies and ontologies (species, cell types, compound nomenclature, treatments, etc) are needed for unambiguous sample annotation
  • Sample annotations in current public databases are typically useless
in perspective
In perspective
  • Standard units for gene expression measurements
  • Standards for sample annotation.
more immediate actions
More immediate actions
  • To understand what information about microarray experiments should be captured to make the descriptions reasonably self-contained
  • Develop data exchange format able to capture this minimum information
  • Develop recommendations how data should be normalised and what controls should be used
mged group
MGED group

The MGED group is an open discussion group initially established at the Microarray Gene Expression Database meeting MGED 1 (14-15 November, 1999, Cambridge, UK). The goal of the group is to facilitate the adoption of standards for DNA-array experiment annotation and data representation, as well as the introduction of standard experimental controls and data normalisation methods. The underlying goal is to facilitate the establishing of gene expression data repositories, comparability of gene expression data from different sources and interoperability of different gene expression databases and data analysis software. Since 1999 the group has had two general meetings and the third one is planned for 2001

For more see www.mged.org

mged participants including
Affymetrix

Berkeley

DDBJ

DKFZ

EMBL

Gene Logic

Incyte

Max Plank Institute

NCBI

NCGR

NHGRI

Sanger Centre

Stanford

Uni Pennsylvania

Uni Washington

Whitehead Institute

MGED participants including
working groups
Working groups
  • Microarray experiment annotations and minimum information standards (A. Brazma)
  • XML-data communication standards and interfaces (P. Spellman)
  • Ontology for sample description (M. Bittner)
  • Cross platform comparison and normalisation (F.Holstege, R.Bumgarner)
  • Future user group - queries, query languages and data mining (M. Vingron)
mged state of art
MGED state of art
  • Formulation of the “minimum information about a microarray experiment” (MIAME) to ensure its interpretability and reproducibility
  • Data exchange format based on XML - microarray markup language (MAML) submitted to OMG in November
miame six parts
MIAME six parts:

1. Experimental design: the set of the hybridisation experiments as a whole

2. Array design: each array used and each element (spot) on the array

3. Samples: samples used, the extract preparation and labeling

4. Hybridizations: procedures and parameters

5. Measurements: images, quantitation, specifications

6. Controls: types, values, specifications

see www.mged.org for details

miame concepts
MIAME concepts
  • MIAME is aimed at co-operative data submitter
  • Concept of “qualifier, value, source” lists, where source is either user defined or an external reference
  • Reusable information can be referenced, but should be provided at least once (array descriptions, standard protocols)
  • Raw data should be reported, together with the authors interpretations
slide25
MAML
  • MAML is an XML based data exchange format able to capture MIAME compliant information
  • The work is still in progress, the first draft has been submitted to OMG as a data exchange standard for microarray data
maml concepts
MAML concepts
  • Annotations + data; data can be given as a set of external 2D matrices
  • Data format independent on particular scanner or image analysis sofwater
  • Sample and treatment can be represented as a DAG
  • Concept of composite images and composite spots
sample and treatment representation
Sample and treatment representation

Sample 1

Sample 2

Sample 3

Treatments

Array 2

Array 1

expression matrix raw and processed

Images

Samples

Genes

Spots

Gene expression levels

Spot/Image quantiations

Expression matrix - raw and processed

microarray image analysis data representation
Microarray image analysis data representation

Spots

Quantitations

composite

spots

primary

spots

Images

composite images

e.g., green/red ratios

primary images

maml future
MAML future
  • The NOMAD microarray LIMS system will export data in MAML format
  • ArrayExpress and GEO will import data in MAML format
  • We hope that OMG will accept MAML as the industry standard
  • We hope that MAML will become a defacto standard
mged steering committee
MGED steering committee
  • Meeting in Bethesda on 17 Nov 2000
  • MIAME accepted and a publication urging the journals and funding agencies to adopt it will be prepared
  • MGED will become ISCB Special Interest Group
  • Next general MGED meeting in Stanford, March 29-31
ad