data analysis department of laboratory medicine university of washington

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Data Analysis Department of Laboratory Medicine University of Washington

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Data Analysis Department of Laboratory Medicine University of Washington Slide 2 Data Analysis Assess data quality Remove artifacts Identify populations Compare with normal Identify abnormal populations Quantitate and evaluate immunophenotype Generate report Slide 3 Assess Data Quality Slide 4 Detector Optimization Negative populations entirely on scale Slide 5 Degeneration Increase SS Decrease FS 08-03307 Slide 6 Degeneration Decrease in intensity for many antigens 08-03307 Slide 7 Viability Gate 08-03307 Slide 8 Viability Gate All cellsViable cells 08-03307 Slide 9 Sample Exhaustion Air in system gives rise to many spurious signals Event gate to exclude non-real events Slide 10 Laser Delay Fluidic instability - Monitor events over time to detect Slide 11 Laser Delay Original Gated Slide 12 Doublet Discrimination Slide 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 Slide 14 Original 07-04513 Example Slide 15 Time 07-04513 Example Slide 16 Singlets 07-04513 Example Slide 17 Viable 07-04513 Example Slide 18 Determining Positivity Slide 19 Incorrect Correct 07-08661 Slide 20 Population Identification Slide 21 Cell Type Identification Lymphocyte population identified by FS/SS gating Slide 22 Cell Type Identification Borowitz et al (1993) AJCP 100:534-40. Steltzer et al (1993) Ann NY Acad Sci 667:265-280 Slide 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 Slide 24 Compare with Normal Slide 25 Normal B cell Maturation Wood and Borowitz (2006) Henrys Laboratory Medicine Slide 26 Follicle Center B cells 08-01359 08-03324 Follicular Lymphoma Follicular Hyperplasia Slide 27 0.1% abnormal immature B cells ALL MRD 06-01469 Slide 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