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Published byRussell Wolfram Modified over 10 years ago
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Department of Laboratory Medicine University of Washington
Data Analysis Department of Laboratory Medicine University of Washington
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Data Analysis Assess data quality Identify populations
Remove artifacts Identify populations Compare with normal Identify abnormal populations Quantitate and evaluate immunophenotype Generate report
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Assess Data Quality
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Detector Optimization
Negative populations entirely on scale
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Degeneration Increase SS Decrease FS
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Degeneration Decrease in intensity for many antigens
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Viability Gate
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Viability Gate All cells Viable cells
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Sample Exhaustion Air in system gives rise to many spurious signals
Event gate to exclude non-real events
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Laser Delay Fluidic instability - Monitor events over time to detect
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Laser Delay Original Gated
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Doublet Discrimination
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Doublet Discrimination
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
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Example Original
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Example Time
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Example Singlets
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Example Viable
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Determining Positivity
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Determining Positivity
Incorrect Correct
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Population Identification
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Cell Type Identification
Lymphocyte population identified by FS/SS gating
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Cell Type Identification
Borowitz et al (1993) AJCP 100: Steltzer et al (1993) Ann NY Acad Sci 667:
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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
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Compare with Normal
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Normal B cell Maturation
Wood and Borowitz (2006) Henry’s Laboratory Medicine
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Follicle Center B cells
Follicular Hyperplasia Follicular Lymphoma
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ALL MRD 0.1% abnormal immature B cells
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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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