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RADical microarray data: standards, databases, and analysis

RADical microarray data: standards, databases, and analysis. Chris Stoeckert, Ph.D. University of Pennsylvania Yale Microarray Data Analysis Workshop December 5, 2003. Science 298:601-604, 2002. Science 298:597-600, 2002. Very few “stemness” genes were common between the two studies. Why?.

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RADical microarray data: standards, databases, and analysis

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  1. RADical microarray data: standards, databases, and analysis Chris Stoeckert, Ph.D. University of Pennsylvania Yale Microarray Data Analysis Workshop December 5, 2003

  2. Science 298:601-604, 2002

  3. Science 298:597-600, 2002

  4. Very few “stemness” genes were common between the two studies. Why? • Inherent problem of testing the stemness hypothesis using a profiling approach? • Summary by Fortunel et al. (Science 2003) who did a third study and found only one common “stemness” gene. • Or did experimental and computational differences reduce the overlap? • ~ 66% overlap if just consider hematopoietic bone marrow samples (Ivanova et al. Science 2003)

  5. To compare experiments, you need some minimum information about the microarray experiments. Ivanova et al. Science 2003 MIAME formalizes that minimum information

  6. MIAME and MAGE are Defined Standards from the Microarray Gene Expression Data (MGED) Society • MIAME - a document which outlines the minimum information that should be reported about a microarray experiment to enable its unambiguous interpretation and reproduction • www.mged.org/miame • Nature Genetics (2001), 29: 365-371. • MAGE - MAGE consists of three parts: An object model (MAGE-OM), a document exchange format, which is derived directly from the object model (MAGE-ML), and software toolkits (MAGE-stk), which seek to enable users to create MAGE-ML • www.mged.org/mage • Genome Biology (2002), 3: research0046.1-0046.9. • In addition, the MGED Ontology provides the language (vocabulary and relationships) for MIAME and MAGE. • www.mged.org/ontology • Comparative & Functional Genomics (2003), 4: 127-132.

  7. Applying MGED Standards • Experiment design: • Name: cell_comparison_design • Type: • development_or_differentiation_design • species_design • cell_type_comparison_design • Experiment Factors: • hematopoietic cell population (LT-HSC, ST-HSC, HSC, LCP, MBC) • Type: BioMaterialCharacteristicCategory: targeted_cell_type • mouse developmental stage (fetal, adult) • Type: BioMaterialCharacteristicCategory: developmental_stage • species (human, mouse) • Type: BioMaterialCharacteristicCategory: organism • stem cell type (hematopoietic, embryonic, neural) • Type: BioMaterialCharacteristicCategory: cell_type MIAME/MAGE info MGED Ontology terms

  8. RAD Enables Use of MGED Standards • RNA Abundance Database (RAD) • http://www.cbil.upenn.edu/RAD • Can search for experiments/studies based on annotations • Graphs automatically generated of study • RAD Study-Annotator for entering annotations • MIAME-based • Incorporates the MGED Ontology • MR_T for exporting in MAGE • Get RAD • All source code available

  9. RAD view of stem cell study

  10. RAD view of stem cell study

  11. RAD view of stem cell study

  12. RAD Study-Annotator collects MIAME and Uses the MGED Ontology

  13. RAD helps you publish! Study-Annotator RAD MAGE-RAD Translator ArrayExpress Journals are requiring deposition of microarray experiments in a public repository.

  14. Patterns of Differential Gene Expression

  15. PaGE • PaGE stands for Patterns from Gene Expression. • A goal is to compare patterns across more than 2 groups to look at co-regulation. • Focuses on fold-change significance as t-statistics not really applicable to describing co-regulation • PaGE was developed by our group at Penn! • Manduchi et al. Bioinformatics 2000. • PaGE uses the False Discovery Rate (FDR). • FDR = # false positives/(# false + true positives) • PaGE takes a minimum confidence level as a parameter, and finds all genes which exceed this confidence. • Each gene is reported with its own confidence. FDR = 1- Confidence • PaGE uses ratios of means. B , C , D A A A Where A, B, C, and D are group means for each gene and A is the reference group. • Use permutations to generate the random distribution of ratios.

  16. Mouse Hematopoietic Stem Cell PaGEs Group B/1 Group C/2 Group D/3 Group A/0

  17. Mouse Hematopoietic Stem Cell PaGEs

  18. StemCellDB: http://stemcell.princeton.edu/v2/ Available real soon!

  19. Summary • Standards • Using MIAME, MAGE, and the MGED Ontology improves your experiment • Databases • Databases like RAD facilitate using standards • Analysis • PaGE provides profiles using differential expression with False Discovery Rate based on ratios.

  20. Acknowledgements • MGED • MIAME, MAGE, and Ontology Working Groups • RAD • Elisabetta Manduchi, Trish Whetzel, Junmin Liu, Angel Pizarro, Greg Grant, Hongxian He, Matt Mailman • PaGE • Greg Grant, Junmin Liu, Elisabetta Manduchi • Stem cells • Ihor Lemischka, Kateri Moore, Natalia Ivanova, Jason Hackney, Laurie Kramer • Hongxian He, Greg Grant, Lyle Ungar

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