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Data Analysis Department of Laboratory Medicine University of Washington.

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Presentation on theme: "Data Analysis Department of Laboratory Medicine University of Washington."— Presentation transcript:

1 Data Analysis Department of Laboratory Medicine University of Washington

2 Data Analysis Assess data quality –Remove artifacts Identify populations Compare with normal –Identify abnormal populations –Quantitate and evaluate immunophenotype Generate report

3 Assess Data Quality

4 Detector Optimization Negative populations entirely on scale

5 Degeneration Increase SS Decrease FS

6 Degeneration Decrease in intensity for many antigens

7 Viability Gate

8 Viability Gate All cellsViable cells

9 Sample Exhaustion Air in system gives rise to many spurious signals Event gate to exclude non-real events

10 Laser Delay Fluidic instability - Monitor events over time to detect

11 Laser Delay Original Gated

12 Doublet Discrimination

13 Doublets = > one cell in laser simultaneously –High cell concentrations –Cell aggregates, sample preparation –High sample aspiration pressure Doublets have composite properties Can exclude using height, area, or width

14 Original Example

15 Time Example

16 Singlets Example

17 Viable Example

18 Determining Positivity

19 Incorrect Correct

20 Population Identification

21 Cell Type Identification Lymphocyte population identified by FS/SS gating

22 Cell Type Identification Borowitz et al (1993) AJCP 100: Steltzer et al (1993) Ann NY Acad Sci 667:

23 Lineage Identification –CD19 for B cells and CD3 for T cells –Assumptions that may not always be correct –Always use at least two methods of identification

24 Compare with Normal

25 Normal B cell Maturation Wood and Borowitz (2006) Henrys Laboratory Medicine

26 Follicle Center B cells Follicular Lymphoma Follicular Hyperplasia

27 0.1% abnormal immature B cells ALL MRD

28 Data Analysis Data displayed as dot plots or histograms –Restrict to subset having high informational content Color discrete populations –Display information from other parameters –Allow rapid visual identification in multiple plots Display data in consistent manner –Pattern recognition


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