Immunology Database and Analysis Portal ImmPort immport

1. Immunology Database and Analysis PortalImmPortwww.immport.org Richard H. Scheuermann, Ph.D. Department of Pathology U.T. Southwestern Medical Center 16 DEC 2010

2. ImmPort Purpose and History • NIH/NIAID/DAIT would like to: • maximize the return on the public investment in basic, translational and clinical research • allow investigators to more effectively extract meaningful information from the vast amounts of data generated from advanced research technologies • => data sharing policy • Bioinformatics Integration Support Contract (BISC) to support data sharing for all DAIT-funded programs - basic, translational and clinical research • Immunology Database and Analysis Portal (ImmPort) - www.ImmPort.org • Archive and manage basic and clinical research data • Integrate these research data with extensive biological knowledge • Support analysis of these integrated data

3. Take-home messages • ImmPort has been tailored to support the needs of the immunology research community • Comprehensive integrated resource for the capture, support and analysis of a wide range of basic, translational and clinical research data • Compliant with established and emerging data standards, e.g. MIAME, MIFlowCyt, Cell Ontology • Work collaboratively with system users to develop and implement novel data processing and analysis methods

4. Tailored for immunology Built by Immunologists for Immunologists Immunologists Bioinformaticians Computational Biologists Biostatisticians Professional Software Developers Built by for Immunologists

5. Vignettes • HLA Region Genetics Consortium • HLA typing ambiguity reduction pipeline • HLA sequence feature definition and variant type analysis and visualization • PyPop-based genetic analysis • Novel methods and infrastructure for flow cytometry analysis – FLOCK • Comprehensive support for clinical and translational research design and results data – Casale/ITN

6. www.immport.org

7. Reference and research data

8. Visualization tools

9. Analysis tools

10. Workspaces • Public • Reference data • Accessible without registration or log in • “Semi-public” • Research data released after publication • Access to analytical tools • Registration and log in required for access • Accessible to all registered users • Private • Pre-publication research data • Access controlled by P.I. (or P.M.) • Collaborative • Controlled sharing of research data

11. Vignettes • HLA Region Genetics Consortium • HLA typing ambiguity reduction pipeline • HLA sequence feature definition and variant type analysis and visualization • PyPop-based genetic analysis • Novel methods and infrastructure for flow cytometry analysis – FLOCK • Comprehensive support for clinical and translational research design and results data – Casale/ITN

12. Summary of SFVT approach • Traditional HLA allele association analysis treats entire allele as a single unit and does not capture the structural relationships between alleles • Sequence Feature Variant Type (SFVT) approach • Define individual sequence features (SF) in HLA proteins (genes) • Determine the extent of polymorphism for each sequence feature by defining the observed variant types (VT) • Re-annotate HLA typing information with complete list of VT for each SF • Examine the association between every sequence feature variant type and disease or other phenotype

13. Representative Sequence Features

14. TCR Binding CD8 Binding A*0201 - ‘CD8 binding’ &‘TCR binding’ SF

15. Summary of SFs defined 1775 total

16. Variant Types for Hsa_HLA-DRB1_beta-strand 2_peptide antigen binding

17. Publication 67F 67I 70D 70D 71R 71R protective risk 28D 28E 26F 26F 30Y 30L 37Y 37F 86V 86G

18. Table of subject vs. HLA 4-digit typing data Table of subject vs. SFVT feature vector Table of p-values, adj. p-values, odds ratio, confidence intervals TCR Binding CD8 Binding ImmPort HLA SFVT Workflow

19. HLA Typing Platforms and Ambiguity • HLA Typing Platforms • SSOP – single-stranded oligonucleotide probe • SSP – sequence-specific priming • SBT – sequence-based typing • SSCP – single-stranded conformation polymorphism • Allelic Ambiguity • Typing methodology cannot distinguish between sets of alleles • Polymorphisms that distinguish these alleles are not interrogated by the method • Outside of exon 2 (class II) or exons 2 and 3 (class I) • Sections of these exons not covered by the probes/primers • Genotypic Ambiguity • Inability to determine phase in heterozygous samples

20. Ambiguity in HLA Typing Data

21. Allelic Ambiguity Reduction Elimination of less-probable alleles by CWD status Reduction of multiple alleles to G- or P-codes Are any of the alleles reg-CWD? Are any of the alleles CWD? Are any of the alleles reg-Rare? no no yes yes yes Eliminate others Eliminate others Eliminate others Do any alleles belong to a common G-code? Do any alleles or G-codes belong to a common P-code? Do the alleles contain any G- or P-codes? no no yes yes yes Combine to G-code Combine to P-code Eliminate rare alleles

22. Outcome of HLA Ambiguity Reduction Allelic Ambiguity Reduction Genotypic Ambiguity Reduction

25. Vignettes • HLA Region Genetics Consortium • HLA typing ambiguity reduction pipeline • HLA sequence feature definition and variant type analysis and visualization • PyPop-based genetic analysis • Novel methods and infrastructure for flow cytometry analysis – FLOCK • Comprehensive support for clinical and translational research design and results data – Casale/ITN

26. Flow Cytometry Analysis FLOCK is an algorithmic application for the identification of unique cell populations in multi-dimensional flow cytometry data A PB GSM GNSM UM3-4 UM1-2 CD27 N1-3 DNM IgD

31. Population statistics

32. Summary Statistics

33. B cell component of the Cell Ontology http://www.obofoundry.org/

34. FlowCAP

35. Vignettes • HLA Region Genetics Consortium • HLA typing ambiguity reduction pipeline • HLA sequence feature definition and variant type analysis and visualization • PyPop-based genetic analysis • Novel methods and infrastructure for flow cytometry analysis – FLOCK • Comprehensive support for clinical and translational research design and results data – Casale/ITN

36. 5+ DAIT-funded Programs Browse Data/ ImmPort Research Data/ ImmPort Supported Programs ImmPort Research Data | My Work Bench Population Genetics Analysis Program: Immunity to Vaccines/Infections Program HLA Region Genetics in Immune-Mediated Diseases Program Immune Function and Biodefense in Children, Elderly, and Immunocompromised Populations Program Immune Modeling Centers Other Consortium Projects Reagent Development for Toll-like and other Innate Immune Receptors DMID-funded Centers of Excellence for Influenza Research and Surveillance GlaxoSmithKline – COPD trial 34 Projects, >100,000 subjects, terabytes of FCM, microarray, SNP genotype, ELISA, ELISPOT, etc. data

37. PopGen Browse Data/ ImmPort Research Data/ ImmPort Supported Programs ImmPort Research Data | My Work Bench Population Genetics Analysis Program: Immunity to Vaccines/Infections Program Grants/Contracts/Projects:

38. Special Pops Browse Data/ ImmPort Research Data/ ImmPort Supported Programs ImmPort Research Data | My Work Bench Immune Function and Biodefense in Children, Elderly, and Immunocompromised Populations Program Grants/Contracts/Projects:

39. Consortium Projects Browse Data/ ImmPort Research Data/ ImmPort Supported Programs ImmPort Research Data | My Work Bench Other Consortium Projects Grants/Contracts/Projects:

40. Study summary

41. Study schematic

42. Study download packages

43. Summary of records for download

44. Download folder of data

45. Links to external resources

46. Data sets - Demographics

47. ImmPort-calculated summary statistics

48. Data sets - Assessments

49. Assessment summaries and links to complete results sets

50. Diastolic Blood Pressure