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RAD3: web forms (lab meeting 9/5/02)

RAD3: web forms (lab meeting 9/5/02). Junmin Liu Elisabetta Manduchi Trish Whetzel. Outline. Overview of RAD3 efforts RAD3: Ontology overview Webforms : General Architecture Registration and Data Preferences From Assay to Quantification Study Design BioMaterial Future Work.

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RAD3: web forms (lab meeting 9/5/02)

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  1. RAD3: web forms(lab meeting 9/5/02) Junmin Liu Elisabetta Manduchi Trish Whetzel

  2. Outline • Overview of RAD3 efforts • RAD3: Ontology overview • Webforms: • General Architecture • Registration and Data Preferences • From Assay to Quantification • Study Design • BioMaterial • Future Work

  3. RAD3 efforts Motivation • Refine the schema to • better suit the MGED efforts (MIAME, MAGE, Ontology, Processing) • incorporate what we have learned from working with this kind of data for a while • Develop protocols and pipeline to overcome various bottlenecks • Assay and Sample annotation • View creation • Raw and processed data loading • Enforce a more complete and curated data loading

  4. RAD3Outcomes • Revamped schema • Fewer views • More structured Biomaterial and Study Design tables • Flexible Data Processing Tables • OntologyEntry • Accurate Database Documentation • Pipeline • Web forms for internal and external use, aimed at providing complete assay and sample annotation • Plugins for internal use • ArrayLoader • ArrayResultLoader • ProcessedResultLoader • LowessNormalizer • Database Population • Curated loading from scratch (no migrations) • Use this to test the new forms and plugins

  5. RAD3 schema and pipeline • Platform Tables (7)  ArrayLoader plugin or Form • Assay to Quantification Tables (9)  Forms I • Study Design Tables (7)  Forms II • BioMaterial Tables (7)  Forms III • Assay Result Tables (2)  ArrayResultLoader plugin • Processing Tables (6)  ProcessedResultLoader and LowessNormalizer plugins • Analysis Result Tables (7) • Misc Tables: Protocol, MAGE, Ontology (6) Core and SRes tables are also largely employed

  6. “Raddies” Greg Grant Hongxian He Junmin Liu Matt Mailman Elisabetta Manduchi Shannon McWeeney (now at OHSU) Angel Pizarro Chris Stoeckert Trish Whetzel

  7. Minimal Information About a Microarray Experiment (MIAME) • Provides the concepts for the ontology • Array design description • Common features of the array as the whole, and the description of each array design elements (e.g., each spot) • Gene expression experiment description • Experimental or Study design • Samples used, extract preparation and labeling • Hybridization procedures and parameters • Measurement data and specifications of data processing • See Brazma et al Nature Genetics 2001 and http://www.mged.org/Workgroups/MIAME/miame.html

  8. OntologyEntry • Purpose • Provide terms and details necessary to create instances of a microarray experiment • Benefits • Known terms with a defined meaning • Minimize free text • Queries can be generated using CV terms

  9. RAD::OntologyEntry Categories • Array Design • Element type • PCR • oligo • Substrate type • nylon • glass • Platform type • spotted cDNA microarray • photolithographic oligo array

  10. RAD::OntologyEntry Categories • Study Design • Replicate • Dose response • Quality control • Normalization • Time series • Study Factor • Methodological Factor • Protocol variation • Hardware variation • Software variation • Operator variation • Biological Factor • disease state • organism part • developmental stage • genetic variation • History Factor

  11. RAD::OntologyEntry Categories • bioMaterial Characteristics • Organism • Contact information for bioMaterial provider • Descriptors relevant to the particular sample, such as • Age • Sex • Developmental stage • Organism part (tissue) • Cell type • Animal/ plant strain or line • Genetic variation (e.g., gene knockout, transgenic variation) • Individual genetic characteristics (e.g., disease alleles, polymorphisms) • Disease state • Clinical information • The individual (for interrelation of the samples in the experiment

  12. WebformsGeneral Architecture • Module based • Written in php4 • Two files per form • Data input accomplished by perl object layer • No deep submits • Front-end data integrity checked by javascript

  13. Assay to Quantification Tables Array Assay RelatedAcquisition Acquisition AcquisitionParam RelatedQuantification Quantification QuantificationParam

  14. Study StudyDesign StudyFactor Study Design Tables StudyAssay StudyDesignDescription StudyDesignAssay Assay StudyFactorValue

  15. BioMaterial: Examples • The brain from one male rat is homogenized, RNA is extracted, split into two parts, one labeled with Cy5, one with Cy3 and used for a self-self hybridization. • Six CD1 female mice are utilized: • Pancreata from each and the liver from four are extracted and homogenized • Two pools are created: pancreas only, liver/pancreas • The first pool is used in a set of 24 self-self hybridizations on 2-channel arrays • The second pool is used in a set of 15 hybridizations on 2-channel arrays where the Cy5-labeled amount is kept constant and the Cy3-labeled amount is varied.

  16. BioMaterial Tables BioMaterialMeasurement BioMaterialCharacteristic Treatment BioMaterialImp LabelMethod BioSource BioSample LabeledExtract AssayLEX AssayBioMaterial Assay

  17. Conclusions Our webforms facilitate data entry into RAD3 and are an important component of our data loading pipeline. The forms reflect the third generation RAD schema as well as the developing ontology concepts. The forms are divided into several modules with flexible entry nodes.

  18. Future Direction • Batch loading of the forms • Update and summary print-out • Graphic navigation through the forms • Help and tutorials

  19. “Raddies” Greg Grant Hongxian He Junmin Liu Matt Mailman Elisabetta Manduchi Shannon McWeeney (now at OHSU) Angel Pizarro Chris Stoeckert Trish Whetzel

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