Genomics LaboratoryUniversity Medical Center Utrecht

External controls & cell count

SP 15 60 180 360 min

Exit from stationary phaseGenes

SP 15 60 180 360 min

...

Microarray technology groupmicroarray production and use

Transcription regulation genome-widehow are genes regulated?

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Bioinformatics groupdatamining & microarray analysis

Utrecht Genomics CenterUniversity Medical Center & Utrecht University

Technology-centered groups/facilitiesBioinformatics

Microarray technologyProteomics

SNP analysisSequencing

Research groupsTranscription regulation genome-wide: Holstege, Timmers

Signal Transduction: Bos, BurgeringDNA replication: van der Vliet

Genetics: WijmengaOncogenomics: Voest

Neurogenomics: Burbach

Temblor participation

WPs pm8.1 – 8.4 6

8.6 4 data annotation tools

8.7 10 populating ArrayExpress

8.9 6 mining ArrayExpress

8.10 6 mining expression data

8.12 4 practical demonstrations

Temblor participation

WPs pm8.1 – 8.4 6

8.6 4 data annotation tools

8.7 10 populating ArrayExpress

8.9 6 mining ArrayExpress

8.10 6 mining expression data

8.12 4 practical demonstrations

Current analysis pipeline

Scanner

Imagene QQCC GeneSpring GeNetLIMS

Gene descriptionsthrough flat files

TIFF images

Flat-files storageRDBMS

Quality ControlNormalization

MIAME compliancy enforcement

XML Database

Advanced analysisVisualization

User path

ArrayDesignMAGE-ML

ExperimentMAGE-ML

Store advanced analysisand visualization

MAGE-ML structure: Array Designs

Features(15552)

Reporters(6378)

Array Design(A-UMCU-1)

Array ManufacturersProtocol

ReporterGroupsGenes

Quality ControlsNormalization Controls

BioSequences(6370)

FeatureReporterMaps

DatabasesSGD

RefSeq

Zones(48)

MAGE-ML structure: Experiments

Experiment(E-UMCU-1)

Array Design(A-UMCU-1)

PhysicalBioAssay(hybridization)

MeasuredBioAssay(Raw data)

DerivedBioAssay(Normalized data)

DerivedBioAssay(Gene Expression Matrix)

Lextract Extract BioSample

BioSource

BioSampleTreatmentTreatment protocol

BioSampleTreatmentLabeling protocol

FeatureExtractionImage analysis protocol

parameters

BioAssayTreatmentHybridization and protocol

DataTransformationQuantitationTypeMapping

DataTransformationQuantitationTypeMapping

BioAssayMappingDesignElementMapping

Experimental Designself vs self, dye swap

Experimental FactorsNormalization controls

DescriptionNormalization

Replicates

Batch

Current analysis pipeline

Scanner

Imagene QQCC GeneSpring GeNetLIMS

Gene descriptionsthrough flat files

TIFF images

Flat-files storageRDBMS

Quality ControlNormalization

MIAME compliancy enforcement

XML Database

Advanced analysisVisualization

User path

ArrayDesignMAGE-ML

ExperimentMAGE-ML

Store advanced analysisand visualization

Data in ArrayExpress

4 experimentshuman cell line serum deprivationhuman cell line heat-shockyeast stationary-phase vs mid-log phaseyeast experimental procedure control experiments

2 array designsyeast 15552 featureshuman 19200 features

11 protocols

Including first fully MIAME compliant submission in MAGE-ML formatvan de Peppel et al., EMBO Reports, 2003

Data underway

Collection of Coelacie patients and controls (33 profiles)

Yeast stationary-phase time course (40 time points)

Yeast responses to copper excess and deprivation (64 time points)

Yeast mutant transcription factors (20 in duplicate)

Collection of head-neck tumor profiles (100 in duplicate)

& >25 projects being run through the microarray facility

Current analysis pipeline

Scanner

Imagene QQCC GeneSpring GeNetLIMS

Gene descriptionsthrough flat files

TIFF images

Flat-files storageRDBMS

Quality ControlNormalization

MIAME compliancy enforcement

XML Database

Advanced analysisVisualization

User path

ArrayDesignMAGE-ML

ExperimentMAGE-ML

Store advanced analysisand visualization

Future pipeline

Scanner

Imagene QQCC GeneSpring GeNet

LIMS

TIFF images

Flat-file storage

RDBMS

Quality ControlNormalization

RDBMS

Advanced analysisVisualization

User path

ArrayDesignMAGE-ML

ExperimentMAGE-ML

BASE

Store raw data in

temporary table

BioConductorR

RDBMS

Low level analysisFiltering

Normalization

Store advanced analysisand visualization

Gene descriptionsthrough Barcode

Raw data annotationMIAME compliancy

Future pipeline

Scanner

Imagene QQCC GeneSpring GeNet

LIMS

TIFF images

Flat-file storage

RDBMS

Quality ControlNormalization

RDBMS

Advanced analysisVisualization

User path

ArrayDesignMAGE-ML

ExperimentMAGE-ML

BASE

Store raw data in

temporary table

BioConductorR

RDBMS

Low level analysisFiltering

Normalization

Store advanced analysisand visualization

Gene descriptionsthrough Barcode

Raw data annotationMIAME compliancy

Temblor participation

WPs pm8.1 – 8.4 6

8.6 4 data annotation tools

8.7 10 populating ArrayExpress

8.9 6 mining ArrayExpress

8.10 6 mining expression data

8.12 4 practical demonstrations

Mining expression data

data tool ArrayExpress

mRNA coexpression na x x

data normalisation x x na

comparing expression-profiles x in progress

~400 expression profiles (time courses)

mRNA coexpression analysis

Find coregulated genes

Combine with other functional genomic data(eg protein interaction, protein localisation, phenotype etc.)

Use for: hypothesis verification, function prediction and data quality assesment

Kemmeren et al., Mol. Cell, 2002

~400 expression profiles (time courses)

mRNA coexpression analysis

Mining expression data

data tool ArrayExpress

mRNA coexpression na x x

data normalisation x x na

comparing expression-profiles x in progress

Microarray controls: subgrid layout

9 external normalization controls in duplicate

5 external ratio controls in duplicatenegative (x-hyb) controls

buffer spots and empty features

Testing external control normalisation

Normalization control spots

Gene spots

Van de Peppel et al., EMBO Reports, 2003

Mining expression data

data tool ArrayExpress

mRNA coexpression na x x

data normalisation x x na

comparing expression-profiles x in progress

med9

sin4

srb11

srb10

srb9

gal11

med3nut1

srb2srb5

med1

srb8 ylr358c

ylr322w

ylr261w

Comparing expression profiles

ylr

26

1w

ylr

35

8c

srb

11

srb

10

srb

9

srb

8

ylr

32

2w

Temblor participation

WPs pm8.1 – 8.4 6

8.6 4 data annotation tools

8.7 10 populating ArrayExpress

8.9 6 mining ArrayExpress

8.10 6 mining expression data

8.12 4 practical demonstrations

Meetings/courses 2003

Organisation/

Month City Country Institute Name of meeting or courseJan Amsterdam NL NKI Technology SeminarFeb Denver USA AAAS Microarrays and Functional GenomicsFeb Leiden NL MGC Yeast to ManMar Hinxton UK EBI Informatics and Analysis of Microarray DataMar Bertinoro Italy EGF 2nd Course in Comparative and Functional GenomicsMar Utrecht NL Astma Fonds Genomics & Proteomics: innovative technologies etcApr Veldhoven NL NAV Yearly meeting dutch anthrpogenetics societyApr Utrecht NL Hubrecht Utrecht BioinformaticsMay Prague CZ ESF Functional genomics and DiseaseMay Amsterdam NL VU YeasterdayJun Heidelberg DE EMBO/EMBL EMBO course microarraysJun Utrecht NL NVBMB Bioinformatics at the interfaceJul Sheffield UK Biochemical Soc. Unravelling nature's networkAug Utrecht NL EPS PhD SummerschoolSep Heidelberg DE EMBO-YIP-PhD YIP PhD courseSep Leuven Bel ESF Microarray data analysis and standardsOct Munich DE Transregio5 Chromatin

External controls & cell count

SP 15 60 180 360 min

Exit from stationary phaseGenes

SP 15 60 180 360 min

...

Microarray facilityDik van LeenenTony MilesMarian Groot-KoerkampJoop van Helvoort

Transcription regulationNynke van BerkumTheo BijmaJeroen van de PeppelNienke KettelarijMarijana RadonjicJean-Christophe AndrauPaul Roepman

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BioinformaticsPatrick KemmerenHarm van BakelPhilip LijnzaadThessa Kockelkorn

Frank HolstegeUniversity Medical Center Utrecht, the Netherlands