rad: christian j. stockert jr, junmin liu

14
The Penn Experience with MAGE-TAB John Brestelli Elisabetta Manduchi Junmin Liu Jonathan Schug Chris Stoeckert NCI MAGE Workshop Jan 24, 2008

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Page 1: RAD: Christian J. Stockert Jr, Junmin Liu

The Penn Experience with MAGE-TAB

John BrestelliElisabetta Manduchi

Junmin LiuJonathan SchugChris Stoeckert

NCI MAGE Workshop Jan 24, 2008

Page 2: RAD: Christian J. Stockert Jr, Junmin Liu

http://www.cbil.upenn.edu/RAD/

Page 3: RAD: Christian J. Stockert Jr, Junmin Liu

Support diabetes research

Page 4: RAD: Christian J. Stockert Jr, Junmin Liu

Support research on protozoan parasites

Page 5: RAD: Christian J. Stockert Jr, Junmin Liu

MAGE-TAB Studies so far …

• Started with MAGE-Tab spec available in 2006 (i.e. before MAGE-Tab v1.0 finalized) and built a framework (MR_Ti) around it by the end of 2006.

• Have loaded 22 studies into RAD (our local database) using MAGE-TAB over the past year.

• MAGE-TAB generated from templates (original submissions) and from downloaded studies.

• Species covered: human, mouse, Plasmodium, Toxoplasma

• Applications covered: expression profiles, chromatin immunoprecipitation, genomic polymorphisms.

Page 6: RAD: Christian J. Stockert Jr, Junmin Liu

Example MAGE-TAB spreadsheet

Page 7: RAD: Christian J. Stockert Jr, Junmin Liu
Page 8: RAD: Christian J. Stockert Jr, Junmin Liu

Lessons Learned

• Positive response from data submittors for spreadsheets.– Provide examples and templates with areas to be filled in colored. – Pretty much use all fields except “release date” and “comment”– 22 studies, 2 are hand-coded by biologists, 4 are generated by

templates which are filled in by biologists. It is very useful from our data loading aspect. But it is hard for biologists to understand the format and manually generate without any help like providing templates.

• Ontology terms provided by curator– Menus were messy and hard to navigate (but probably could be

overcome technically)• Adaptable to non-array technologies

– Final touches on a complicated Taqman study on ES cell differentiation protocols

Page 9: RAD: Christian J. Stockert Jr, Junmin Liu

Do MAGE-TAB templates have to follow MAGE-TAB specifications?

Of course, but the biologists filling them out don’t need to know that!

Page 10: RAD: Christian J. Stockert Jr, Junmin Liu

MAGE-TAB Tools and Process

• Methods used for MAGE-Tab generation – Manually generate a MAGE-Tab – MAGE-Tab template then convert to MAGE-Tab– MAGE-ML, convert to MAGE-Tab using mage2tab developed by

us.– GEO-Importer, MAGE-Tab converter (from ArrayExpress)

• Mage2graph: visualization

• Mage-checker: validation

• LoadMageDoc plugin

Page 11: RAD: Christian J. Stockert Jr, Junmin Liu

Handling MAGE docs in unified way

processors

validators

translator

O/R layer

GUS DB

mage doc

Mage doc in other formats

graph

common objects

ontology matrix

Page 12: RAD: Christian J. Stockert Jr, Junmin Liu

MR_Ti overviewReader

Processor

Validator

Translator

Study->submit

Reporter

Tester

VO’

VO

VO

GusObj

MagemlReader

MageTabReader

SoftReader

BaseProcessor

ProcessModuleMergeTreatmentSerialsNamingBioSamplesNamingScans

BaseValidator

ValidationRuleProtocolHasMageTypeStudyDesignHasMageTypeAssayHasFactorValues

makeServiceFactroy

GUSCommit

MR_Tilogger

SqlReporter

SqlTester

Config.xmlread-in

use

use

use

use

use

use

MR_TiException

VoToGusTranslator

VoToMageTabVoToDot

Page 13: RAD: Christian J. Stockert Jr, Junmin Liu

MAGE-TAB Tools and ProcessInitial contact with investigator/Review publication

Provide appropriate MAGE-TAB template

Get filled in template

Download SOFT files from GEO/ Review publication

If Affymetrix, use ArrayExpress converter tool to generate MAGE-Tab;

if cDNA array, in-house script to generate template

.

Review tab files and fill in protocols, experimental

factors, ontology terms as needed.

Validate, load, and check graph

MAGE-ML filesFrom ArrayExpress

Convert to MAGE-Tab using mage2tabConvert to MAGE-Tab

using template2tab

Page 14: RAD: Christian J. Stockert Jr, Junmin Liu

DetailsEPConDB• 2904 Survivin transgenic mice pancreatic islet profile (MAGE-ML)• 2929 Genome-wide location analysis of HNF Transcription Factors in Hepatocytes and Pancreatic Islets (MAGE-ML)• 2944 Sox4 null mice e12.5 pancreas (templates)• 3021 Neurogenin3 deficiency and Embryonic Pancreatic Gene Expression (SOFT)• 3042 Foxa2 controls vesicle docking and insulin secretion in mature beta-cells (generated by PIs)• 3061 Gene expression profiling of Nkx2-2 Mutant and Wild-Type - e12.5 and e13.5 Pancreata (templates)• 3100 Gene expression profiling in the endocrine pancreas (templates)• 3121 Gene expression profiling of MafA, MafB, and MafA/MafB Mutants in E18.5 pancreas (templates)

T1Dbase• 3144 Expression data from NOD-scid vs B6-scid pancreas, submandibular glands, & lacrimal glands (SOFT)• 3203 Gene expression in PBMCs from children with diabetes (SOFT)

PlasmoDB (SOFT)• 21 Molecular mechanism for switching of P.falciparum invasion pathways into human erythrocytes • 22 P.falciparum strain 3D7, SIR2 knockout• 23 Invasion by P. falciparum merozoites suggests a hierarchy of molecular interactions• 29 Regulation of sexual development of Plasmodium by translational repression.• 51 Expression profile of 3D7 clones 3D7AH1S2 and 3D7S8.4 at ring, trophozite and schizont stages.• 52 CD36 panned clones• 55 Identification of genome wide gene copy number polymorphisms in Plasmodium falciparum• 64 Tetracyclines Specifically Target the Apicoplast of the Malaria Parasite Plasmodium falciparum• 85 Whole genome analysis of mRNA decay in P. falciparum• 161 Plasmodium falciparum W2/Dd2 Day 8 gametocytes

ToxoDB (generated by PIs)• 42 Expression profiling of the 3 archetypal T. gondii lineages• 101 Effects of Glucose Starvation in Toxoplasma gondii