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2013 Duke CFAR Flow Cytometry Workshop. Data Analysis. Results from Pre-Workshop Analysis Comp Profile. Results from Pre-Workshop Analysis. Results from Pre-Workshop Analysis. Results from Pre-Workshop Analysis. Results from Pre-Workshop Analysis. Elements of Data Analysis. - PowerPoint PPT Presentation
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2013 Duke CFAR Flow Cytometry Workshop
Data Analysis
Results from Pre-Workshop Analysis
Comp Profile
Results from Pre-Workshop Analysis
Results from Pre-Workshop Analysis
Results from Pre-Workshop Analysis
Results from Pre-Workshop Analysis
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)
• Training
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)
• Training
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 TNFa response. It is visually apparent that, while all labs had overcompensation, it is worst in labs with the lowest cytokine responses.
Inaccurate Automated Compensation:Requirement for Manual Adjustment
JO AnalysisAutocomp FlowJo
A700-PCPCy5.5 = 29.32
JO AnalysisModified comp FlowJo
A700-PCPCy5.5 = 6
HM analysisDiva (Lab J)
CD28
PCP
-Cy5
.5
CD3 A700
JO AnalysisModified comp FlowJo
A700-PCPCy5.5 = 6&
PCPCy5.5-PEA610 = 235
Note: Green laser excitation for both PerCPCy5.5 & PEA610
Compensation: Inspect and Manually Correct as Needed
PE-PEA610= 12.87
PE-PEA610= 11
Auto Manually adjusted
EQAPOL: example of
compensation affecting cytokine results
Comp Profile
Orig
inal
Mat
rix(A
uto-
com
p)
“Cor
rect
ed”
Mat
rix(A
uto-
com
pw
/ M
anua
l tw
eaki
ng)
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
Compensation Cannot Correct Spreading Error
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)
• Training
No Biexponential Transformation:Off-scale Negative Affects Gate Placement
0 102
103
104
105
<B515-A>: IFNg FITC
0
102
103
104
105
<G71
0-A>
: CD4
CY5
5PE
20.6
0 10 2 10 3 10 4 10 5
<B515-A>: IFNg FITC
0
10 2
10 3
10 4
10 5
<G71
0-A>
: CD4
CY5
5PE
41
Original gate Revised gate
IFNFITC
CD
4 PE
-C
y5.5
FlowJo v8.3.3 (Rm 120 G5): BiExponential Transformation of Specimen 1 Tube 1 (Unstim) CD4+ Gate
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)
• Training
CIC Gating Panel: Gating Recommendations
CIC Gating Panel: Gating Recommendations (examples of adequate analysis)
CIC Gating Panel: Gating Recommendations (examples of inadequate analysis)
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)
• Training
EQAPOL: example of backgates showing CD3 dim+ excluded from gate
BeforeBackgate
AfterBackgate
IFNgBackgate
CD3 AmCyan
Excl
usio
n
0.38 5.74
CD4 Gated CD8 Gated
5.230.27
IFNg PE-Cy7
CD4
PerC
P-Cy
5.5
CD8
APC-
Cy7
BeforeBackgate
AfterBackgate
A
B
BACKGATING: purity & recovery
Duke University Medical Center
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)
• Training
Intra-Operator Comparison: Original Analysis
N=5 FTE analyzing8 stims12 colors
Intra-Operator Comparison: Original Analysis
N=5 FTE analyzing8 stims12 colors
Intra-Operator Analysis:12 Color ICS NM Analysis - CD3+ Lymphocytes Gated
0 102
103
104
105
<B515-A>: IFNg FITC
0
102
103
104
105
<G71
0-A>
: CD4
CY5
5PE
20.6
0 10 2 10 3 10 4 10 5
<B515-A>: IFNg FITC
0
10 2
10 3
10 4
10 5
<G71
0-A>
: CD4
CY5
5PE
41
Original gate Revised gate
IFNFITC
CD
4 PE
-C
y5.5
Intra-Operator AnalysisBefore & After Correcting CD4- & CD8- Gates
original
final
Created in V6.4.2Opened & copied in V6.4.6-looks correct
Created in V6.4.6Opened & 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)
Intra-Operator Analysis Before & After FlowJo Manual Transformation
Intra-Operator Comparison:Functional
Values
Gating Strategy
FSC-W
FSC-
H
88.3
<V705-A>: CD8 Q705
<G71
0-A>
: CD4
CY5
5PE
57.8
36.3
0.79
FSC-A
SSC-
A
99.3
<Violet G-A>: CD3 Amcyan
<Vio
let H
-A>:
vAm
ine
CD14
PB C
D19
PB
41.4
Gating Strategy for 11-Color Maturation/Function Panel: 1 of 3
CD4
PerC
P-Cy
5.5
SSC-
A
Excl
usio
n (V
iole
t H)
FSC-
H
FSC-ACD3 AmCyanFSC-W
CD8 Alexa700
Ungated Singlets CD3+ Exclusion-
Scatter
Basic Gates:
CD4+CD8-
CD8+CD4-
CD4+CD8+
- 3 total
Duke University Medical Center
<G66
0-A>
: CD2
7 CY
5PE
43 54.1
2.580.33
<G66
0-A>
: CD2
7 CY
5PE
56.4 28.6
8.466.55
<V54
5-A>
: CD
57 Q
545 0.12 1.07
55.942.9
<V54
5-A>
: CD5
7 Q
545
5.67 13.2
24.256.9
Gating Strategy for Sampson 11-Color Maturation/Function Panel: 2 of 3
<G66
0-A>
: CD2
7 CY
5PE
22 62.5
11.73.98
<V54
5-A>
: CD5
7 Q
545 3.98 22.9
51.721.5
CD57
FIT
C
CD57
FIT
C
CD57
FIT
C
CD27
APC
-Ale
xa75
0
CD27
APC
-Ale
xa75
0
CD27
APC
-Ale
xa75
0
CD45RO ECD
N
NN
CM
CMCM
EM
EM
EM
TE
TETE
E
EE
Maturational Gates:
CD4+CD8-
CD8+CD4-CD4+CD8+
CD45RO ECD
CD45RO ECD
Naive Central Memory
EffectorMemory
Terminal Effector Effector
Naive Central Memory
EffectorMemory
Terminal Effector Effector
Naive Central Memory
EffectorMemory
Terminal Effector Effector
- 5 per basic subset
Duke University Medical Center
<R710-A>: CD107a AX680
2.59CD107
Gating Strategy for Sampson 11-Color Maturation/Function Panel: 3 of 3
Functional & Boolean Gates:
- 4 functional gates per maturational subset
CM: CD8+CD4-
1.14
IL-2
TNF-a
IFN-
0.31
4.19
Duke University Medical Center
Backgate!
<R710-A>: CD107a AX680
2.59CD107
Gating Strategy for Sampson 11-Color Maturation/Function Panel: 3 of 3
Functional & Boolean Gates:
- 4 functional gates per maturational subset - 16 boolean gates per maturational subset
CM: CD8+CD4-
Boolean Gates
Polyfunctional (1: ++++)
Polyfunctional (4: +++)
Bifunctional (6: ++)
Monofunctional (4: +)
Nonfunctional (1: ----)
Key:7 = CD107g = IFN-2 = IL-2T = TNF-a
1.14
IL-2
TNF-a
IFN-
0.31
4.19
Duke University Medical Center