PHANG LAB TALK

1. PHANG LAB TALK Tzu L Phang Ph.D. Assistant Professor Department of Medicine Division of Pulmonary Sciences & Critical Care Medicine

2. What I do: • Perform high-throughput data analysis for the scientific community; microarray and Next Generation Sequencing datasets • Provide analysis solution for experts and novice users alike • Develop multi-media approaches to disseminate translational science education • Studying the role of long non-coding RNA; second talk • Establishing the Bioinformatics Consultation and Analysis Core to help researchers and scientists design, analyze and interpret their experiments.

3. Today’s Talk Layout • The center of my universe: • R and Bioconductor • Collaboration with Biologists • 5x5; simple way to teach and contribute • Next Generation Sequencing (NGS)

4. Today’s Talk Layout • The center of my universe: • R and Bioconductor • Collaboration with Biologists • 5x5; simple way to teach and contribute • Next Generation Sequencing (NGS)

5. R r-project.org

6. R is hot http://blog.revolutionanalytics.com/r-is-hot/

7. R in the media

8. Bioconductor • www.bioconductor.org • Statistical tools in R for high-throughput data analysis • 6 month update cycle. Release 2.10 with 554 software package (45 new) • Analysis workflow • Oligonucleotide Arrays • Sequence Analysis • Variants • Accessing Annotation Data • High-throughput Assays

9. The Websitewww.bioconductor.org

10. Categories

11. Categoriescont …

12. Typical Analysis Routine

13. R is easy 

14. Result output

15. Other Resources http://www.statmethods.net/ http://www.rseek.org/ http://crantastic.org/ http://stackoverflow.com/

16. Today’s Talk Layout • The center of my universe: • R and Bioconductor • Collaboration with Biologists • 5x5; simple way to teach and contribute • Next Generation Sequencing (NGS

17. Collaboration • >1000 microarray chips / year • Affymetrix & Illumina platforms • Next Generation Sequencing 25 free Pilot Projects. • Serve the rocky mountain region scientific community

18. Collaboration - tips • Don’t be a data analyst – be a co-investigator • Suggest analysis approaches that are not obvious • Focus on the result, not method • Always looks for grant writing opportunity • Understand the technical & biological system as thoroughly as possible – you will be surprise what biologists missed informatically

19. Exmaple 1: Classification of Pituitary Tumors • Pituitary tumors are the most common type of brain tumor in 20% at autopsy and 1/10,000 persons clinically. Based upon 2010 figures of a veteran population of 22.7 million, this translates into >225,000 veterans with pituitary tumors. • Currently no medical therapies exist for these tumors and surgical resection is the treatment of choice. Recurrence rates approach 40%. • Understanding of the pathways to tumorigenesis and markers of aggressiveness and risk of recurrence would alter the intensity and cost of clinical care and may provide novel candidates and pathways to explore for new treatment options for these patients

21. Principle Component Analysis

22. Potential markers

23. Outputs

24. Example 2: Explore the artistic side!

26. Example 3: Unconventional Usage

28. Introduction • Crohn’s Disease (CD) is an Inflammatory Bowel Disease (IBD) that affecting up to one million Americans (15 to 30 ages). • Discordance between monozygotic twins affected by CD provide evidence for epigenetic role in etiology of disease. • We combined 2 microarray technologies to study these roles • CHARM array (Comprehensive High-throughout Array for Relative Methylation) • Gene Expression (Affymetix Gene 1.0 ST)

31. Research Informatics Integrated Core (RIIC) Michael G. Kahn MD, PhD CCTSI Co-Director & RIIC Core Director Michael.Kahn@ucdenver.edu

32. RIIC Organizational Model

33. http://cctsi.ucdenver.edu/RIIC/Pages/ConsultationDataAnalysis.aspxhttp://cctsi.ucdenver.edu/RIIC/Pages/ConsultationDataAnalysis.aspx

36. 5X5http://cctsi.ucdenver.edu/5x5

37. Demonstration http://gcrc.ucdenver.edu/Videos/Informatics/5x5/SocialNetworking5x5.wmv

38. Tools

39. Podcast

41. TIES – Translational Informatics Education Support (TIES) • Bridging the gap in translational research through education • Training biologist informatics • Enhance collaboration through education and knowledge exchange • Bring awareness in latest technical advances • Disseminate knowledge through innovation

42. Next Generation Sequencing The future is here ….

43. High Throughput Parallel Sequencing • http://www.youtube.com/watch?v=77r5p8IBwJk

45. Paradigm Shift • Standard “Sanger” sequencing • 96 sample/day • Read length ~650 bp • Total = 450,000 bases of sequence data • 454 – the game changer! • ~400,000 different templates (reads)/day • Read length ~ 250 (at that time) • Total = 100,000,000 bases of sequence data

46. The second generation Roche (454) http://454.com/ • First on the market • Emulsion PCR and pyrosequencing Illumina (Solexa) http://www.illumina.com/ • Second on the market • Bridge PCR and polymerase based SBS Abi(Solid) http://solid.appliedbiosystems.com/ • Third on the market • Emulsion PCR and ligase based sequencing

47. Single molecule sequencing • Helicos Biosciences • http://helicosbio.com • true Single Molecule Sequencing technology • Pacific Biosciences • http://www.pacificbiosciences.com • Single Molecule Real Time sequencing

48. Portable Sequencer • Ion Torrent

49. Others • Polonator http://www.polonator.org • Emulsion PCR and ligase based sequencing • Used in the Personal Genome Project • Open platform, open source • Cheap/affordable • Complete Genomics http://www.completegenomics.com • Specializing in human genome sequencing

50. Type of read data • Base Space or Color Space • Paired end or single end • Stranded or Unstranded