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The GOAL…
“That our differential expression data will
be an accurate representation of the
biological system measured, and...
The GOAL…
my BELIEF…
“That if I do not pay enough attention to
experimental design and quality control,
those colleagues w...
Variability in Label-Free Proteomics
Workflows
Sample Prep
Data Collection
Minimize
and
Measure
Variability!
Sample Prep: Procedure and Pitfalls
Lysis
Normalization
Digestion
SPE/Desalting
Dry and Reconstitute
Detergent/Chaotrope
P...
Sample Prep: Controlling for Variability
Lysis
Normalization
Digestion
SPE/Desalting
Dry and Reconstitute
Controlling for ...
How to Assess Variability of a Workflow
Zhang, Fenyo, and Neubert. J. Proteome
Res. 2009, 8(3): 1285-1292
Method 2 (Neuber...
Limiting and Measuring Variability in LC-MS/MS
Analysis (Exemplar with n=6 Samples)
“Technical-Replicate Heavy”
Incorrect ...
Limiting and Measuring Variability in LC-MS/MS
Analysis (Exemplar with n=6 Samples)
“Singles + QC Pool”
Technical Variance...
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Asms qc Will Thompson Duke

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ASMS 2014 Analytical Core Directors Workshop. Presented by Will Thompson http://www.genome.duke.edu/cores/proteomics/contact/will-thompson/

Published in: Science, Education, Technology
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Asms qc Will Thompson Duke

  1. 1. The GOAL… “That our differential expression data will be an accurate representation of the biological system measured, and that our colleagues who develop clinical diagnostics will find the data credible.”
  2. 2. The GOAL… my BELIEF… “That if I do not pay enough attention to experimental design and quality control, those colleagues will never believe me.” “That our differential expression data will be an accurate representation of the biological system measured, and that our colleagues who develop clinical diagnostics will find the data credible.”
  3. 3. Variability in Label-Free Proteomics Workflows Sample Prep Data Collection Minimize and Measure Variability!
  4. 4. Sample Prep: Procedure and Pitfalls Lysis Normalization Digestion SPE/Desalting Dry and Reconstitute Detergent/Chaotrope Physical Stress mL/mg volume ratios Bradford/BCA/A280 Assay Constant protein content Constant volume Substrate concentration Constant Enz/Substrate Ratio Fresh reagents Mixing/Temperature/Time Enzyme Quality? Online/offline Commercial/Homemade Avoid where possible Speedvac/Lyophilize Solubility? Avoid where possible
  5. 5. Sample Prep: Controlling for Variability Lysis Normalization Digestion SPE/Desalting Dry and Reconstitute Controlling for variability Constant mass/volume ratios Constant Volume and [Protein] Protein Standards (SIL or “surrogate”) Peptide Standards (SIL or “surrogate”)
  6. 6. How to Assess Variability of a Workflow Zhang, Fenyo, and Neubert. J. Proteome Res. 2009, 8(3): 1285-1292 Method 2 (Neubert et al) 𝑆2 𝑡𝑜𝑡𝑎𝑙 = 𝑆2 1 + 𝑆2 2 + 𝑆2 3 …+𝑆2 𝑛 Method 1 (‘old school’) Biological Technical (Preparation) Analytical . . . .
  7. 7. Limiting and Measuring Variability in LC-MS/MS Analysis (Exemplar with n=6 Samples) “Technical-Replicate Heavy” Incorrect (Underestimation) Correct “Moderate Technical Replication” (“90/10 approach”) “Singles + QC Pool” Analysis Order: 1. Randomization (if unknowns) 2. “Blocking” + Randomization (if known sample grouping)
  8. 8. Limiting and Measuring Variability in LC-MS/MS Analysis (Exemplar with n=6 Samples) “Singles + QC Pool” Technical Variance (%CV) Biological Variance (%CV) 0 5 10 15 20 25 30 35 2 3 4 5 6 7 8 9 10 Average%CV Number of Peptides Biological Variance (Avg) Technical Variance (Avg) 0 200 400 600 800 1000 5 15 25 35 45 55 65 75 85 95 PeptideCount % CV Biological Variance Technical Variance

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