1. 2013 Duke CFAR Flow Cytometry Workshop Data Analysis

2. NCMEMTEE Pre-Vaccination 33% 21% 27% 2% 17% Post-Vaccination 8% 48% 25% 2% 17% Duke University Medical Center Reproducible analysis allows us to measure an expansion of CD4+ CM cells post vaccination with some degree of confidence

3. Site Remediation: Summary of Findings 3 Timeliness Viability/Recovery Annotation Instrument Setup Analysis Gating Including debris/dead cells/monocytes in gates Including Monocyte population - TNFa backgrounds Not including all of anchor gate populations Not including dim positives in anchor gate populations Setting cytokine gates too close/too far from negative Failing to backgate FlowJo Versions Performance (processor) Bugs

4. Elements of Data Analysis Compensation – electronic adjustment for spectral overlap – When to compensate Acquisition – if gating on #CD3+, requires compensation Off-line – Spillover Biexponential Transformation Gates Analysis Regions Backgating – used to tweak gates and analysis regions so as to optimize response (maximize positive and minimize negative responses) Acceptability criteria Inter-operator variability

5. Elements of Data Analysis Compensation – electronic adjustment for spectral overlap – When to compensate Acquisition – if gating on #CD3+, requires compensation Off-line – Spillover Biexponential Transformation Gates Analysis Regions Backgating – used to tweak gates and analysis regions so as to optimize response (maximize positive and minimize negative responses) Acceptability criteria Inter-operator variability

6. Spectral Overlap http://flowbook.denovosoftware.com

7. 7 Compensation Cannot Correct Spreading Error

8. Spectral Overlap http://flowbook.denovosoftware.com

9. Compensation: Inspect and Manually Correct as Needed PE-PEA610 = 12.87 PE-PEA610 = 11 Auto Manually adjusted

10. Compensation: False Positive CD4 Response to CEF Pepmix mSA EOLm

11. Compensation: False Positive CD4 Response to CEF Pepmix

12. Compensation matrix Define New Matrix Wizard Upload matrix

13. 1. Compensation matrix

14. Original Matrix (Auto-comp) “Corrected” Matrix (Auto-comp w/ Manual tweaking) Note 1: Compensation pairs discussed during the call are marked with pink arrows. Red arrows indicate other compensation pairs I felt could benefit from manually tweaking compensation values. Note 2: flowjo automatically flags manual edits using red text; all other differences are flowjo doing weird rounding/display stuff (ex. for PEA610-PE “590” is really “59.36;” the value has not been modified… this drives me NUTS! Original vs Manually-tweaked FlowJo Compensation Values

15. 2. Comp Profile

16. 3. Manually Adjust Compensation

17. Elements of Data Analysis Compensation – electronic adjustment for spectral overlap – When to compensate Acquisition – if gating on #CD3+, requires compensation Off-line – Spillover Biexponential Transformation Gates Analysis Regions Backgating – used to tweak gates and analysis regions so as to optimize response (maximize positive and minimize negative responses) Acceptability criteria Inter-operator variability

18. CIC Gating Panel: Gating Recommendations

19. B (3.4%) F (10.5%) E (13.4%) D (10.2%)K (9.4%) G (16.9%) C (3.1%)A (6.8%) H (10.2%) I (12.7%) J (4.8%) Here labs are listed in order of their total TNF  response. It is visually apparent that, while all labs had overcompensation, it is worst in labs with the lowest cytokine responses.

20. FlowJo v8.3.3 (Rm 120 G5): BiExponential Transformation of Specimen 1 Tube 1 (Unstim) CD4+ Gate

21. Elements of Data Analysis Compensation – electronic adjustment for spectral overlap – When to compensate Acquisition – if gating on #CD3+, requires compensation Off-line – Spillover Biexponential Transformation Gates Analysis Regions Backgating – used to tweak gates and analysis regions so as to optimize response (maximize positive and minimize negative responses) Acceptability criteria Inter-operator variability

22. Intra-Operator Comparison: Original Analysis N=5 FTE analyzing 8 stims 12 colors

23. No Biexponential Transformation: Off-scale Negative Affects Gate Placement 010 2 3 4 5 : IFNg FITC 0 10 2 3 4 5 : CD4 CY55PE 20.6 010 2 3 4 5 : IFNg FITC 0 10 2 3 4 5 : CD4 CY55PE 41 Original gateRevised gate IFN  FITC CD4 PE-Cy5.5

24. Intra-Operator Analysis Before & After Correcting CD4 - & CD8 - Gates original final

25. Created in V6.4.2 Opened & copied in V6.4.6 -looks correct Created in V6.4.6 Opened & copied in V6.4.6 -looks bad Intra-Operator Analysis: Same data file created in different FlowJo versions but pasted from the exact same FlowJo File (preferences identical)

26. Intra-Operator Analysis Before & After FlowJo Manual Transformation

27. Intra-Operator Comparison: Functional Values

28. CIC Gating Panel: Gating Recommendations

29. CIC Gating Panel: Gating Recommendations (examples of adequate analysis)

30. CIC Gating Panel: Gating Recommendations (examples of inadequate analysis)

31. Elements of Data Analysis Compensation – electronic adjustment for spectral overlap – When to compensate Acquisition – if gating on #CD3+, requires compensation Off-line – Spillover Biexponential Transformation Gates Analysis Regions Backgating – used to tweak gates and analysis regions so as to optimize response (maximize positive and minimize negative responses) Acceptability criteria Inter-operator variability

32. Backgating: Include CD3dim+ cells in gate

33. Before Backgate After Backgate IFNg Backgate CD3 AmCyan Exclusion 0.385.74 CD4 GatedCD8 Gated 5.23 0.27 IFNg PE-Cy7 CD4 PerCP-Cy5.5 CD8 APC-Cy7 Before Backgate After Backgate A B BACKGATING: purity & recovery Duke University Medical Center

34. Backgating: Include CD8dim+ in gate

35. Site Remediation Example 1: High TNFa background from monocytes 35 SA EOLm Time vs. FSC-A FSC-W vs. FSC-H Aqua vs. SSC-A CD3 vs. SSC-A CD4 vs. CD8 CD3 vs. TNFa

36. Site Remediation Example 2: Cytokine gate too close to negative 36 Site Re-Analysis Site Analysis EOLm Unstim CEF (0.006 – 0.065) (0.452 - 0.720) EOLm Range (background subtracted)

37. Site Remediation Example 3: FlowJo bug - Display does not match calculated value 37 Site Analysis EOLm Unstim CEF (0.000 – 0.053) (0.124 – 0.308) EOLm Range (background subtracted)

38. Time Gate

39. Gating Strategy

40. Elements of Data Analysis Compensation – electronic adjustment for spectral overlap – When to compensate Acquisition – if gating on #CD3+, requires compensation Off-line – Spillover Biexponential Transformation Gates Analysis Regions Backgating – used to tweak gates and analysis regions so as to optimize response (maximize positive and minimize negative responses) Acceptability criteria Inter-operator variability

41. Acceptability Criteria Viability ≥ 80% (DAIDS IQA) Recovery 80 – 120% (DAIDS IQA) Sufficient number of events – 120,000 CD3+ (EQAPOL) – 200 polyfunctional Repetitive Values (DAIDS IQA) – Basic subsets: Range ≤5 – Activation/Maturation: Range ≤10 T cell check (3=4+8) (DAIDS IQA) LymphoSum (L = T+B+NK) (DAIDS IQA) Positive Controls – greater than antigen-specific Negative Controls - ≤0.05% Replicate sample testing - one response category for ICS assays – 0.06 – 0.09 (very low) – 0.10 – 0.49 (low) – 0.5 – 0.99 (medium) – ≥1.0 (high)

42. Elements of Data Analysis Compensation – electronic adjustment for spectral overlap – When to compensate Acquisition – if gating on #CD3+, requires compensation Off-line – Spillover Biexponential Transformation Gates Analysis Regions Backgating – used to tweak gates and analysis regions so as to optimize response (maximize positive and minimize negative responses) Acceptability criteria Inter-operator variability