Meeting the Bioinformatics Challenges of Functional...
Transcript of Meeting the Bioinformatics Challenges of Functional...
Meeting the Bioinformatics Meeting the Bioinformatics Challenges of Functional Challenges of Functional
GenomicsGenomicsVanBUGVanBUG
11 September 200311 September 2003
The TIGR Gene Index TeamThe TIGR Gene Index TeamFoo CheungFoo Cheung
Svetlana KaramychevaSvetlana KaramychevaYudan LeeYudan Lee
Babak ParviziBabak ParviziGeo PerteaGeo Pertea
Razvan SultanaRazvan SultanaJennifer TsaiJennifer Tsai
John QuackenbushJohn QuackenbushJoseph WhiteJoseph White
Funding provided by the Department of EnergyFunding provided by the Department of Energyand the National Science Foundationand the National Science Foundation
TIGR Human/Mouse/ArabidopsisTIGR Human/Mouse/ArabidopsisExpression TeamExpression Team
Emily ChenEmily ChenBryan FrankBryan Frank
Renee GaspardRenee GaspardJeremy HassemanJeremy Hasseman
Lara LinfordLara LinfordFenglong LiuFenglong LiuSimon KwongSimon Kwong
John QuackenbushJohn QuackenbushShuibang WangShuibang WangYonghong WangYonghong Wang
Ivana YangIvana YangYan YuYan Yu
Array Software Hit TeamArray Software Hit TeamNirmal BhagabatiNirmal Bhagabati
John BraistedJohn BraistedTracey CurrierTracey Currier
Jerry LiJerry LiWei LiangWei Liang
John QuackenbushJohn QuackenbushAlexander I. SaeedAlexander I. Saeed
Vasily SharovVasily SharovMathangi ThiagarajanMathangi Thiagarajan
Joseph WhiteJoseph WhiteAssistantAssistantSue MineoSue MineoFunding provided by the National Cancer Institute,Funding provided by the National Cancer Institute,
the National Heart, Lung, Blood Institute,the National Heart, Lung, Blood Institute,and the National Science Foundationand the National Science Foundation
H. Lee Moffitt Center/USFH. Lee Moffitt Center/USFTimothy J. YeatmanTimothy J. Yeatman
Greg BloomGreg Bloom
TIGR PGA CollaboratorsTIGR PGA CollaboratorsNorman LeeNorman LeeRenae MalekRenae Malek
HongHong--Ying WangYing WangTruong LuuTruong Luu
Bobby BehbahaniBobby Behbahani
<[email protected]><[email protected]>AcknowledgmentsAcknowledgments
PGA CollaboratorsPGA CollaboratorsGary Churchill (TJL)Gary Churchill (TJL)Greg Evans (NHLBI)Greg Evans (NHLBI)Harry Gavras (BU)Harry Gavras (BU)
Howard Jacob (MCW)Howard Jacob (MCW)Anne Kwitek (MCW)Anne Kwitek (MCW)Allan Pack (Penn)Allan Pack (Penn)
Beverly Paigen (TJL)Beverly Paigen (TJL)Luanne Peters (TJL)Luanne Peters (TJL)
David Schwartz (Duke)David Schwartz (Duke)
EmeritusEmeritusJennifer Cho (TGI)Jennifer Cho (TGI)
Ingeborg Holt (TGI)Ingeborg Holt (TGI)Feng Liang (TGI)Feng Liang (TGI)
KristieKristie Abernathy (Abernathy (µµAA))Sonia Dharap (Sonia Dharap (µµAA))
Julie EarleJulie Earle--Hughes (Hughes (µµAA))Cheryl Gay (Cheryl Gay (µµAA))Priti Hegde (Priti Hegde (µµAA))
Rong Rong QiQi ((µµAA))Erik Snesrud (Erik Snesrud (µµAA))Heenam Kim (Heenam Kim (µµAA))
TIGR Faculty, IT Group, and StaffTIGR Faculty, IT Group, and Staff
<[email protected]><[email protected]>AcknowledgmentsAcknowledgments
Thanks to Thanks to SyntekSyntek, Inc. , Inc. <http://<http://www.syntek.comwww.syntek.com>>
for for GeneShavingGeneShaving MeV module and assistance MeV module and assistance with with MyMADAMMyMADAM
Thanks to Thanks to DataNautDataNaut, Inc. , Inc. <http://<http://www.datanaut.comwww.datanaut.com>>
for for RelNetRelNet and Terrain Map modules and and Terrain Map modules and assistance with Client/Server MeVassistance with Client/Server MeV
Science is built with facts as a house is with Science is built with facts as a house is with stones stones –– but a collection of facts is no more a but a collection of facts is no more a science than a heap of stones is a house.science than a heap of stones is a house.
–– Jules Henri Jules Henri PoincarePoincare
There are 10There are 101111 stars in the galaxy. That stars in the galaxy. That used to be a huge number. But it's only a used to be a huge number. But it's only a hundred billion. It's less than the national hundred billion. It's less than the national deficit! We used to call them astronomical deficit! We used to call them astronomical
numbers. Now we should call them numbers. Now we should call them economical numbers.economical numbers.
-- Richard Richard FeynmanFeynman, physicist, Nobel laureate , physicist, Nobel laureate (1918(1918--1988)1988)
Microarray Analysis at TIGRMicroarray Analysis at TIGR
Step 1: Experimental DesignStep 1: Experimental Design
Step 2: Data CollectionStep 2: Data Collection
Step 3: Data AnalysisStep 3: Data Analysis
Step 4: Consulting with the Step 4: Consulting with the ArraySWArraySW gang in the trailergang in the trailer
Step 5: Sharing data with our collaboratorsStep 5: Sharing data with our collaborators
Steps in the ProcessSteps in the ProcessSelect array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Steps in the ProcessSteps in the ProcessSelect array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
TIGR Gene Indices TIGR Gene Indices home page home page
www.tigr.org/tdb/tgiwww.tigr.org/tdb/tgi
~60 species~60 species
>16,000,000 sequences>16,000,000 sequences
☺☺ Available with sourceAvailable with source
Geo PerteaGeo PerteaRazvan SultanaRazvan Sultana
Valentin AntonescuValentin Antonescu
TGICL Tools are available TGICL Tools are available –– with more comingwith more coming
Gene Index Assembly processGene Index Assembly process
High stringency pairHigh stringency pair--wise comparisons to wise comparisons to
buildbuild ClustersClusters
reduce reduce redundancyredundancy
Expressed Transcripts (ET)Expressed Transcripts (ET)from GenBank CDSfrom GenBank CDS
remove vector, polyremove vector, poly--A, A, adapter,mitochondrial adapter,mitochondrial
and ribosomal sequenceand ribosomal sequence
ESTs from ESTs from GenBank GenBank (dbEST)(dbEST)
TIGR ESTsTIGR ESTs
Each cluster is Each cluster is assembled to obtainassembled to obtain
Tentative Tentative ConsensusConsensus
sequences (sequences (TCTCs)s)
Annotate TCs Annotate TCs and releaseand release
The Mouse Gene IndexThe Mouse Gene Index <http://<http://www.tigr.org/tdb/mgiwww.tigr.org/tdb/mgi>>
A TC ExampleA TC Example
Babak ParviziBabak Parvizi
GO Terms GO Terms and EC Numbersand EC Numbers
The TIGR Gene IndicesThe TIGR Gene Indices <http://<http://www.tigr.org.tdb/tdb/tgiwww.tigr.org.tdb/tdb/tgi>>
Dan Lee, Ingeborg HoltDan Lee, Ingeborg Holt
Building Building TOGsTOGs: Reflexive, Transitive Closure
Tentative OrthologuesTentative Orthologues
And ParaloguesAnd Paralogues
: Reflexive, Transitive Closure
Thanks to Thanks to WoytekWoytek MakałowskiMakałowski and Mark Boguski and Mark Boguski
TOGA: An Sample Alignment: TOGA: An Sample Alignment: bithoraxoidbithoraxoid--like proteinlike protein
Gene Finding in Humans is easy!Gene Finding in Humans is easy!
Razvan SultanaRazvan Sultana
Gene Finding in HumansGene Finding in Humans is easy?is easy?
Razvan SultanaRazvan Sultana
Gene Finding in Humans is difficult?Gene Finding in Humans is difficult?
Razvan SultanaRazvan Sultana
Gene Finding in HumansGene Finding in Humans is difficult?is difficult?
Razvan SultanaRazvan Sultana
A genome and its annotation is A genome and its annotation is onlyonly a a hypothesis that must be tested.hypothesis that must be tested.
RESOURCERER RESOURCERER Jennifer TsaiJennifer Tsai
http://http://pga.tigr.org/tools.shtmlpga.tigr.org/tools.shtml
RESOURCERER: An ExampleRESOURCERER: An Example
RESOURCERER: Using Genetic MarkersRESOURCERER: Using Genetic Markers
Just added: Integrated QTLsJust added: Integrated QTLs
Steps in the ProcessSteps in the ProcessSelect array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
SOPs are availableSOPs are available Coming: Data QC SOPComing: Data QC SOP
<http://<http://pga.tigr.org/tools.shtmlpga.tigr.org/tools.shtml>>
cDNA/template prepcDNA/template prep PCR purificationPCR purification
PrintingPrinting RNA labelingRNA labeling
HybridizationHybridization
What data should we collect?What data should we collect?Nature GeneticsNature Genetics 29, December 200129, December 2001
<http://<http://www.mged.orgwww.mged.org>>MAGEMAGE--ML ML –– XMLXML--based data exchange formatbased data exchange format
EVERYTHINGEVERYTHING
An Example of “MIAME-lite”
MIAME Relational SchemaMIAME Relational Schema
What’s Wrong with MIAME?MIAME was designed as a model for capturing information MIAME was designed as a model for capturing information necessary to create public databases.necessary to create public databases.
MIAMEMIAME--based databases lack LIMS capabilities, which are based databases lack LIMS capabilities, which are necessary for largenecessary for large--scale studies.scale studies.
We do not want to store images in our database for We do not want to store images in our database for practical reasons practical reasons –– limited space.limited space.
We needed to develop a variety of tools adapted to our We needed to develop a variety of tools adapted to our existing infrastructure and existing infrastructure and legacy data and databaseslegacy data and databases..
Probes are labeled and applied to the arraysProbes are labeled and applied to the arraysAn “experiment” is a hybridizationAn “experiment” is a hybridizationA “study” is a collection of hybridization experimentsA “study” is a collection of hybridization experiments
MAD Microarray Database SchemaMAD Microarray Database Schema
Conceptual Schema: MADConceptual Schema: MAD
ProtocolProtocolPrimer_pairPrimer_pair
PrimerPrimer
PCRPCR
New_plateNew_plateSlideSlide Slide_typeSlide_type SpotSpot
ScanScan AnalysisAnalysis NormalizeNormalize
ExperimentExperiment ExpressionExpression
Expt_probeExpt_probe
HybHyb
StudyStudy
ProbeProbe Probe_sourceProbe_source
GeneGene
CloneClone
MADAM: Microarray Data Manager
☺☺ ☺☺ MarieMarie--Michelle Michelle CordonnierCordonnier--Pratt, UGAPratt, UGAconverted converted MySQLMySQL to Oracle and madeto Oracle and madeMADAM work!MADAM work!
MADAM: Microarray Data Manager
☺☺ Available with source and Available with source and MySQLMySQL
ExpDesignerExpDesigner
MAGE OM for Array DataMAGE OM for Array Data
•• Purpose: Provide and object model to capture Purpose: Provide and object model to capture data for a MIAME data repository.data for a MIAME data repository.
•• Accept data in XML format from any database, Accept data in XML format from any database, i.e. schema independent.i.e. schema independent.
•• Load data into MIAME database.Load data into MIAME database.•• Export data from MIAME database in XML format. Export data from MIAME database in XML format.
MIAMEMADMAD
XML Formatted DocumentXML Formatted Document
MAGE OMMAGE OM
THE INSTITUTE FOR GENOMIC RESEARCHTHE INSTITUTE FOR GENOMIC RESEARCHTIGRTIGRTIGR
Steps in the ProcessSteps in the ProcessSelect array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Microarray Overview IMicroarray Overview I
MicrobialORFs
Design PCR Primers
PCR Products
EukaryoticGenes
Select cDNA clones
PCR ProductsFor each plate set,For each plate set,many identical replicasmany identical replicas
Microarray SlideMicroarray Slide(with 60,000 or more(with 60,000 or more
spotted genes)spotted genes)
+
Microtiter PlateMicrotiter Plate
Many different plates Many different plates containing different genescontaining different genes
Microarray OverviewMicroarray Overview
PCR AmplificationPCR Amplification
Selected GenesSelected Genes
Primer DesignPrimer Design
GelGel--based Scoringbased Scoring
Primer SynthesisPrimer Synthesis
MAD
PCR ScorerPCR ScorerReads/loads primer data file Reads/loads primer data file
to MAD and allows PCR data entry,to MAD and allows PCR data entry,and translation of 96and translation of 96 ⇒⇒ 384.384.
(Alex Saeed, developer and maintainer(Alex Saeed, developer and maintainerenhancements: Wedge Smith)enhancements: Wedge Smith)
Clone SelectionClone Selection
The Beast: Microarray Robot from Intelligent AutomationThe Beast: Microarray Robot from Intelligent Automation<http://<http://www.ias.comwww.ias.com>>
Additional Software for Arrays: SchedulerAdditional Software for Arrays: SchedulerMicroarray SchedulerMicroarray Scheduler
Allows scheduling Allows scheduling of all instrumentsof all instruments
Designed and maintained Designed and maintained by Jerry Li by Jerry Li
☺☺ Available with sourceAvailable with source
Microarray OverviewMicroarray Overview
MAD
Amplified/Purified GenesAmplified/Purified Genes
Loaded in ArrayerLoaded in Arrayer
Slides PrintedSlides Printed
Run Parameters SetRun Parameters Set
SliTrackSliTrack/Controller/ControllerTakes Slide Order Takes Slide Order
and Run parameters,and Run parameters,generates spot order,generates spot order,
IAS control file,IAS control file,launches IAS run software,launches IAS run software,
loads database.loads database.(J. Li, developer and maintainer)(J. Li, developer and maintainer)
Steps in the ProcessSteps in the ProcessSelect array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Microarray Overview IIMicroarray Overview II
Hybridize,Hybridize,WashWash
MeasureMeasureFluorescenceFluorescencein 2 channelsin 2 channels
redred//greengreen
Analyze the dataAnalyze the datato identifyto identifypatterns ofpatterns of
gene expressiongene expression
Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Microarray Overview IIMicroarray Overview II
Hybridize,Hybridize,WashWash
MeasureMeasureFluorescenceFluorescencein 2 channelsin 2 channelsredred//greengreen
Analyze the dataAnalyze the datato identifyto identifypatterns ofpatterns of
gene expressiongene expression
WeedWeed
BushBush
Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Microarray Overview IIMicroarray Overview II
Hybridize,Hybridize,WashWash
MeasureMeasureFluoresenceFluoresencein 2 channelsin 2 channels
red/greenred/green
Analyze the dataAnalyze the datato identify to identify
differentiallydifferentiallyexpressed genesexpressed genes
Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Obtain RNA SamplesObtain RNA Samples
Microarray OverviewMicroarray Overview
MAD
MADAMMADAMAllows data entryAllows data entry
(J. Li & J. White, web prototype;(J. Li & J. White, web prototype;A. Saeed, J. White, J.Li, A. Saeed, J. White, J.Li, & V. Sharov, developers)& V. Sharov, developers)
Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Hybridize,Hybridize,WashWashObtain RNA SamplesObtain RNA Samples
Microarray OverviewMicroarray Overview
MAD
MABCOSMABCOSUses Bar Codes to track samplesUses Bar Codes to track samples
(J. Li developer)(J. Li developer)
Obtain RNA SamplesObtain RNA Samples Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Hybridize,Hybridize,WashWash
☺☺ Available with sourceAvailable with source
Microarray OverviewMicroarray OverviewPaired TIFFPaired TIFFImage FilesImage Files
MADAM + MADAM + µµMAPMAPAllows data entry, Allows data entry,
moves files/renames to moves files/renames to longlong--term storageterm storage
(A. Saeed, J. White, J.Li, (A. Saeed, J. White, J.Li, & V. Sharov, developers)& V. Sharov, developers)
MAD
NetAPP
Microarray OverviewMicroarray Overview
NetAPP
Spotfinder Spotfinder Provides Image Analysis, Provides Image Analysis,
writes data towrites data toflat files or directly to dbflat files or directly to db
(V. Sharov, developer and maintainer)(V. Sharov, developer and maintainer)
MAD
☺☺ Available as Executable for Windows;Available as Executable for Windows;devicedevice--independent C/C++ comingindependent C/C++ coming
The TIGR Array Software System
SLITRACK
MADAM
PCRSCORE
ExpDesigner
SpotFinder
MABCOS
McCoder
MeVMIDASMAD
Data Normalization and FilteringData Normalization and Filtering
Lowess NormalizationLowess NormalizationWhy LOWESS?Why LOWESS?
-3
-2
-1
0
1
2
3
7 8 9 10 11 12 13 14
log(Cy3*Cy5)
A SD = 0.346
ObservationsObservations1.1. IntensityIntensity--dependent structuredependent structure2.2. Data not mean centered at logData not mean centered at log22(ratio) = 0(ratio) = 0
LOWESS (Cont’d)LOWESS (Cont’d)
Local linear regression model Local linear regression model
TriTri--cube weight function cube weight function
Least Squares
Estimated Estimated values of values of loglog22(Cy5/Cy3) as (Cy5/Cy3) as function of function of loglog1010(Cy3*Cy5)(Cy3*Cy5)
Least Squares
WYXWXX
xyxw
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1
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∑
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βββ
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ββ
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-3
-2
-1
0
1
2
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7 8 9 10 11 12 13 14
log(Cy3*Cy5)
AA SD = SD = 0.3460.346
LOWESS Results
“Slice Analysis” (Intensity-dependent Z-score)
MIDAS: Data AnalysisMIDAS: Data Analysis Wei LiangWei Liang
Adding Error Models,Adding Error Models,MAANOVA,MAANOVA,
Automated ReportingAutomated Reporting
☺☺ Available with OSI sourceAvailable with OSI source
Microarray OverviewMicroarray Overview
MAD
MAD
MIDAS MIDAS Performs data normalizationPerforms data normalizationand filtering, including, soon, ANOVAand filtering, including, soon, ANOVA
MIDASMIDAS
Steps in the ProcessSteps in the ProcessSelect array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
MeV: Data Mining ToolsMeV: Data Mining Tools
☺☺ Available with OSI sourceAvailable with OSI source
Alexander SaeedAlexander SaeedAlexander Alexander SturnSturnNirmal BhagabatiNirmal Bhagabati
John BraistedJohn BraistedSyntekSyntek Inc.Inc.
DatanautDatanaut, Inc., Inc.
MeV: Metabolic pathway analysis is comingMeV: Metabolic pathway analysis is coming
Maria Klapa and Chris KoenigMaria Klapa and Chris Koenig
Analyses available in MeV...Hierarchical clustering (HCL)Hierarchical clustering (HCL)Bootstrapped/Jackknifed HCLBootstrapped/Jackknifed HCLkk--means clustering (KMC)means clustering (KMC)kk--means support (iterative KMC)means support (iterative KMC)SelfSelf--Organizing Maps (Organizing Maps (SOMsSOMs))Cluster Affinity Search Technique (CAST)Cluster Affinity Search Technique (CAST)Figure of Merit for CAST and KMC (soon SOM)Figure of Merit for CAST and KMC (soon SOM)QTQT--clustclust ((HeyerHeyer Jackknife)Jackknife)Principal component analysis (PCA)Principal component analysis (PCA)Gene ShavingGene ShavingRelevance NetworksRelevance NetworksSupport Vector Machines (SVM)Support Vector Machines (SVM)SelfSelf--Organizing TreesOrganizing TreesClassification approaches, including Template MatchingClassification approaches, including Template Matchingtt--teststestsSignificance Analysis of Microarrays (SAM)Significance Analysis of Microarrays (SAM)
ANOVA toolsANOVA toolsGO, Metabolic Pathway, and Genome Localization annotation/clusteGO, Metabolic Pathway, and Genome Localization annotation/clusteringring
ClientClient--server mode with wellserver mode with well--defined APIdefined API
Missing from MeV...MAGEMAGE--ML output for direct submission to ML output for direct submission to databases ... Coming in the next MADAM release.databases ... Coming in the next MADAM release.
Links to Links to BioConductorBioConductor …… are coming.are coming.
Array CGH module from Barb Weber and Adam Array CGH module from Barb Weber and Adam Margolin ... is coming.Margolin ... is coming.
EASE module from Doug Hosack ... is comingEASE module from Doug Hosack ... is coming
Lots of stuff we are not smart enough to think Lots of stuff we are not smart enough to think about.about.
Sleep Deprivation Studies in MouseSleep Deprivation Studies in Mouse00 33 66 99 1212
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Experimental ParadigmExperimental ParadigmCompare gene expression between sleeping and Compare gene expression between sleeping and sleepsleep--deprived mice in cortex and hypothalamusdeprived mice in cortex and hypothalamus
Perform 3 biological replicatesPerform 3 biological replicates
Normalize and filter data and use data mining techniques Normalize and filter data and use data mining techniques to select distinct patterns of gene expressionto select distinct patterns of gene expression
Use Gene Ontology (GO) assignments to classify genes Use Gene Ontology (GO) assignments to classify genes by cellular localization, molecular function, biological by cellular localization, molecular function, biological processprocess
Use GO analysis to develop an understanding of responseUse GO analysis to develop an understanding of response
Differential Expression in CortexDifferential Expression in Cortex
Energy MetabolismTranscription;Mitochondrial and Ribosomal Proteins
Stress Response
IntermediateMetabolism andSignal Transduction
Differential Expression in HypothalamusDifferential Expression in Hypothalamus
Sleep signaling
EASE Analysis of GO termsEASE Analysis of GO termsCortex – Up-regulated Genes
GO Class GO Category p-value GO Cellular Component endoplasmic reticulum 6.06×10-03
GO Molecular Function heat shock protein activity 8.78×10-04
pyruvate dehydrogenase (lipoamide) phosphatase activity 3.17×10-03
chaperone activity 7.38×10-03
Cortex – Down-regulated Genes
GO Class Gene Category p-value GO Biological Process protein biosynthesis 2.85×10-25
protein metabolism 1.00×10-11
electron transport 6.04×10-03
GO Cellular Component ribosome 5.95×10-37
ribonucleoprotein complex 1.17×10-32
eukaryotic 48S initiation complex 9.74×10-18
eukaryotic 43S pre-initiation complex 2.68×10-15
mitochondrial inner membrane 3.70×10-03
GO Molecular Function structural constituent of ribosome 6.46×10-39
RNA binding activity 4.83×10-21
cytochrome c oxidase activity 9.79×10-04
hydrogen ion transporter activity 1.88×10-03
ThemesThemes: : General biological trends based on representation of General biological trends based on representation of functional roles on the arrayfunctional roles on the arrayProblemProblem: : Requirement of functional class assignment limits utility Requirement of functional class assignment limits utility for discovery of new functional networksfor discovery of new functional networks
Hosack, Hosack, et al. 2003et al. 2003 Thanks to Doug Hosack, NIAIDThanks to Doug Hosack, NIAID
Now available... The TGI databases, including RESOURCERERThe TGI databases, including RESOURCERER
The TGICL Gene Index Clustering and Assembly ToolsThe TGICL Gene Index Clustering and Assembly Tools
A freelyA freely--available available MySQLMySQL version of our MIAMEversion of our MIAME--supportive databasesupportive database
A freelyA freely--available, open source, javaavailable, open source, java--based set of tools:based set of tools:MADAM: MADAM: MMicroicroaarray rray DaData ta MManager anager MIDAS: MIDAS: MiMicroarray croarray DData ata AAnalysis nalysis SSystemystemMeV: MeV: MMultiultieexperimentxperiment VVieweriewer
A freelyA freely--available, image processing software system available, image processing software system linked to the database: TIGR linked to the database: TIGR SpotfinderSpotfinder
Nobody in the game of football Nobody in the game of football should be called a genius. should be called a genius.
A genius is somebody like Norman Einstein. A genius is somebody like Norman Einstein.
--Joe Joe TheismanTheisman, Former quarterback, Former quarterback
A theory has only the possibility of being A theory has only the possibility of being right or wrong. A model has a third right or wrong. A model has a third
possibility; it may be right but irrelevant.possibility; it may be right but irrelevant.
–– Manfred Manfred EigenEigen
Unless a reviewer has the courage Unless a reviewer has the courage to give you unqualified praise, I say to give you unqualified praise, I say
ignore the bastard.ignore the bastard.
-- John John SteinbeckSteinbeck
The TIGR Gene Index TeamThe TIGR Gene Index TeamFoo CheungFoo Cheung
Svetlana KaramychevaSvetlana KaramychevaYudan LeeYudan Lee
Babak ParviziBabak ParviziGeo PerteaGeo Pertea
Razvan SultanaRazvan SultanaJennifer TsaiJennifer Tsai
John QuackenbushJohn QuackenbushJoseph WhiteJoseph White
Funding provided by the Department of EnergyFunding provided by the Department of Energyand the National Science Foundationand the National Science Foundation
TIGR Human/Mouse/ArabidopsisTIGR Human/Mouse/ArabidopsisExpression TeamExpression Team
Emily ChenEmily ChenBryan FrankBryan Frank
Renee GaspardRenee GaspardJeremy HassemanJeremy Hasseman
Heenam KimHeenam KimLara LinfordLara Linford
Simon KwongSimon KwongJohn QuackenbushJohn Quackenbush
Shuibang WangShuibang WangYonghong WangYonghong Wang
Ivana YangIvana YangYan YuYan Yu
Array Software Hit TeamArray Software Hit TeamNirmal BhagabatiNirmal Bhagabati
John BraistedJohn BraistedTracey CurrierTracey Currier
Jerry LiJerry LiWei LiangWei Liang
John QuackenbushJohn QuackenbushAlexander I. SaeedAlexander I. Saeed
Vasily SharovVasily SharovMathangi Mathangi ThaiagarjianThaiagarjian
Joseph WhiteJoseph WhiteAssistantAssistantSue MineoSue MineoFunding provided by the National Cancer Institute,Funding provided by the National Cancer Institute,
the National Heart, Lung, Blood Institute,the National Heart, Lung, Blood Institute,and the National Science Foundationand the National Science Foundation
H. Lee Moffitt Center/USFH. Lee Moffitt Center/USFTimothy J. YeatmanTimothy J. Yeatman
Greg BloomGreg Bloom
TIGR PGA CollaboratorsTIGR PGA CollaboratorsNorman LeeNorman LeeRenae MalekRenae Malek
HongHong--Ying WangYing WangTruong LuuTruong Luu
Bobby BehbahaniBobby Behbahani
<[email protected]><[email protected]>AcknowledgmentsAcknowledgments
PGA CollaboratorsPGA CollaboratorsGary Churchill (TJL)Gary Churchill (TJL)Greg Evans (NHLBI)Greg Evans (NHLBI)Harry Harry GavarasGavaras (BU)(BU)
Howard Jacob (MCW)Howard Jacob (MCW)Anne Kwitek (MCW)Anne Kwitek (MCW)Allan Pack (Penn)Allan Pack (Penn)
Beverly Paigen (TJL)Beverly Paigen (TJL)Luanne Peters (TJL)Luanne Peters (TJL)
David Schwartz (Duke)David Schwartz (Duke)
EmeritusEmeritusJennifer Cho (TGI)Jennifer Cho (TGI)
Ingeborg Holt (TGI)Ingeborg Holt (TGI)Feng Liang (TGI)Feng Liang (TGI)
KristieKristie Abernathy (Abernathy (mAmA))Sonia Sonia Dharap(mADharap(mA))
Julie EarleJulie Earle--Hughes (Hughes (mAmA))Cheryl Gay (Cheryl Gay (mAmA))Priti Hegde (Priti Hegde (mAmA))
Rong Rong QiQi ((mAmA))Erik Snesrud (Erik Snesrud (mAmA))
TIGR Faculty, IT Group, and StaffTIGR Faculty, IT Group, and Staff