1. RTI International RTI International is a trade name of Research Triangle Institute. www.rti.org Designing a high quality metabolomics experiment Grier P Page Ph.D. Senior Statistical Geneticist RTI International Atlanta Office gpage@rti.org 770-407-4907

2. RTI International Metabolomics is Powerful and Central

3. RTI International Designing a good study

4. RTI International RTI International is a trade name of Research Triangle Institute. www.rti.org Errors Errors Everywhere

5. RTI International

6. UMSA Analysis Insulin Resistant Insulin Sensitive Day 1 Day 2

7. RTI International  Understand the strengths and weaknesses of each step of the experiments.  Take these strengths and weaknesses into account in your design. Primary consideration of good experimental design

8. RTI International RTI International is a trade name of Research Triangle Institute. www.rti.org

9. From Drug Discov Today. 2005 Sep 1;10(17):1175-82.

10. RTI International State the Question and Articulate the Goals

11. RTI International The Myth That Metabolomics does not need a Hypothesis  There always needs to be a biological question in the experiment. If there is not even a question don’t bother.  The question could be nebulous: What happens to the metabolome of this tissue when I apply Drug A.  The purpose of the question is to drive the experimental design.  Make sure the samples answer the question: Cause vs. effect.

12. RTI International

13. Design Issues  Known sources of non-biological error (not exhaustive) that must be addressed – Technician / post-doc – Reagent lot – Temperature – Protocol – Date – Location – Cage/ Field positions

14. RTI International Experimental Design

15. RTI International Biological replication is essential.  Two types of replication – Biological replication – samples from different individuals are analyzed – Technical replication – same sample measured repeatedly  Technical replicates allow only the effects of measurement variability to be estimated and reduced, whereas biological replicates allow this to be done for both measurement variability and biological differences between cases. Almost all experiments that use statistical inference require biological replication.

16. RTI International How many replicates?  Controlled experiments – cell lines, mice, rats 8-12 per group.  Human studies – discovery 20+ per group  For predictive models – 100+ per group, need model building and validation sets  The more the better, always.

17. RTI International Experimental Conduct All experiments are subject to non- biological variability that can confound any study

18. RTI International Control Everything!  Know what you are doing  Practice!

19. RTI International What if you can’t control or make all things uniform  Randomize  Orthogonalize

20. RTI International What are Orthogonalization and Randomization ?  Orthogonalization- spreading the biological sources of error evenly across the non-biological sources of error. – Maximally powerful for known sources of error.  Randomization – spear the biological sources of error at random across the non-biological sources of error. – Useful for controlling for unknown sources of error

21. RTI International Examples of Orthogonalization and Randomization ? Sample #TreatmentVariety 111 212 311 412 521 622 721 822 OrderSample 11 22 35 46 58 67 74 83 OrderSample 17 26 34 41 52 68 75 83 The experiment Orthogonalize Randomize

22. RTI International RTI International is a trade name of Research Triangle Institute. www.rti.org Statistical analyses have assumptions too

23. RTI International Statistical analyses  Supervised analyses – linear models etc – Assume IID (independently identically distibuted) – Normality – Sometimes can rely on central limit – ‘Weird’ variances – Using fold change alone as a statistic alone is not valid. – ‘Shrinkage’ and or use of Bayes can be a good thing.  False-discovery rate is a good alternative to conventional multiple-testing approaches.  Pathway testing is desirable.

24. RTI International Classification  Supervised classification – Supervised-classification procedures require independent cross-validation. – See MAQC-II recommendations Nat Biotechnol. 2010 August ; 28(8): 827–838. doi:10.1038/nbt.1665.  Wholly separate model building and validation stages. Can be 3 stage with multiple models tested  Unsupervised classification – Unsupervised classification should be validated using resampling-based procedures.

25. RTI International Unsupervised classification - continued  Unsupervised analysis methods – Cluster analysis – Principle components – Separability analysis  All have assumptions and input parameters and changing them results in very different answers

26. RTI International

28. Sample size estimation for metabolomics studies

29. RTI International There is strength in numbers — power and sample size.  Unsupervised analyses – Principal components, clustering, heat maps and variants – These are actually data transformations or data display rather than hypothesis testing, thus unclear if sample size estimation is appropriate or even possible. – Stability of clustering may be appropriate to think about. Garge et al 2005 suggested 50+ samples for any stability.

30. RTI International Sample size in supervised experiments  Supervised analyses – Linear models and variants – Methods are still evolving, but we suggest the approach we developed for microarrays may be appropriate for metabolomics (being evaluated)

31. RTI International

33. RTI International is a trade name of Research Triangle Institute. www.rti.org Metabolomics does not reveal everything and different technologies show different things

34. RTI International  Technology and detection evolves over time.

35. RTI International Technologies are not perfect in agreement

36. RTI International The human urine metabolome

37. RTI International Sample, Image and Data Quality Checking

38. RTI International

43. Metabolite quality  Still evolving field  RTI is one of the Metabolomics Reference Standards Synthesis Centers

44. RTI International Know your data - What should it look like

45. These are OK

46. These are not OK

47. RTI International One bad sample can contaminate an experiment

48. Histogram of p-values

49. Potentially Bad Data

50. Histogram of p-values with bad data removed

51. RTI International Quality of Database, Bioinformatics and Interpretative tools

52. RTI International  Just because a database says something does not mean it is right. Read the evidence.  Databases are biased.  Databases are incomplete  Databases have lots of data  Understand data before you use it  Database are useful! Understand what databases include, don’t include, and assumptions

53. RTI International RTI International is a trade name of Research Triangle Institute. www.rti.org Issues in the Annotation of Genes, proteins, metabolites

54. RTI International Annotation is inconsistent across sources

55. RTI International RTI International is a trade name of Research Triangle Institute. www.rti.org Issues with pathway data

56. RTI International

57. TCA cycle from Ingenuity

58. TCA from GeneMAPP

59. TCA cycle from Ingenuity

60. RTI International RTI International is a trade name of Research Triangle Institute. www.rti.org Share Your Data Use shared data!

61. RTI International Metabolomics WorkBench  http://www.metabolomicsworkbench.org/

62. RTI International MetaboLights

63. RTI International  Practice compendium research – to allow others to replicate your work  Many high profile omic studies are not even technically reproducible Overshare your data and show work

64. RTI International  Limited in the literature so far. Some work on tissue and species metabolomes. Use metabolomics databases

65. RTI International  Design your experiment well  Conduct your experiment well  Control for non-biological sources of error  Know what is good and bad quality data at each stage including metabolite, image, data, and annotation  If you are aware of these issues and control for them highly powerful and reproducible metabolite experimentation is possible.  Else you get garbage  Share your data and use shared data Summary

66. RTI International  The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray based predictive models. Nat Biotechnol. 2010 August ; 28(8): 827–838.  Microarray data analysis: from disarray to consolidation and consensus. Nat Rev Genet. 2006 Jan;7(1):55-65.Nat Rev Genet.  Baggerly K. "Disclose all data in publications." Nature. 2010 Sep 23;467(7314):401. PMID: 20864982  Repeatability of published microarray gene expression analyses. Nat Genet. 2009 Feb;41(2):149-55 Nat Genet.  A design and statistical perspective on microarray gene expression studies in nutrition: the need for playful creativity and scientific hard-mindedness. Nutrition. 2003 Nov-Dec;19(11-12):997- 1000. Nutrition.  39 Steps. From Drug Discov Today. 2005 Sep 1;10(17):1175-82. References

67. If time allows

68. RTI International RTI International is a trade name of Research Triangle Institute. www.rti.org RTI Regional Comprehensive Metabolomics Resource Core (RTI RCMRC) Susan Sumner, PhD Director RTI RCMRC Discovery Sciences Proteomics and Metabolomics Programs RTI International

69. Contact Information for the RTI RCMRC Susan C.J. Sumner, PhD Director RTI RCMRC Senior Scientist nanoSafety RTI International Discovery Sciences 3040 Cornwallis Drive Research Triangle Park North Carolina 27709 ssumner@rti.org 919-541-7479 (office) 919-622-4456 (cell) Jason P. Burgess, PhD Program Coordinator, RTI RCMRC Associate Director, Discovery Sciences RTI International 3040 Cornwallis Drive Research Triangle Park North Carolina 27709 jpb@rti.org 919-541-6700 (office)

70. RTI International MS and NMR Instruments at RTI and DHMRI RTIDHMRI Mass Spectrometers (38) LC-MS 136 GC-MS 43 GC x GC-TOF-MS 11 ICP-MS 61 MALDI ToF/ToF 21 NMR (6) 24

71. RTI International Some RTI Metabolomics Applications and Pilots Experience with adolescent and adult human subject research, animal model and cell based research, e.g.,  Apoptosis- cells  Drug induced liver injury- animal models  in utero exposure to chemicals and fetal imprinting- animal models  Dietary exposure and imprinting- animal models  NAFLD - pediatric obesity; microbiome  Weight Loss- pediatric obesity  Preterm delivery- human subjects  Response to vaccine- human subjects  Nicotine withdrawal- human subjects  Colon cancer- human subjects

72. RTI International Pilot and Feasibility Studies  The aim of the pilot and feasibility program is to foster collaborations and promote the use of metabolomics.  Studies will be selected through an application process. – Application involves abstract, description of samples available (matrix type, volume, type and duration of storage, sample processing, freeze thaws, etc), description of phenotypes, and plan for subsequent grant/contract submissions for metabolomics analysis beyond initial pilot study.  Applications may also include technology development.  Applications must agree to deposit data in DRCC, coauthor publications, and submit joint grant/contract proposals.  Deadlines being defined