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Controlling and Measuring Variation
in Sample Preparation and Data
Analysis in a Core Facility
Environment
Christopher Colangelo
Director of Protein Profiling
MS & Proteomics Resource
Yale University
June 17, 2014
Analytical Lab Managers Interest Group
ASMS – Baltimore, MD
Sources of Technical Variability in Quantitative LC-MS
Proteomics: Human Brain Tissue Sample Analysis
Piehowski et. al. J. Proteome Res. 2013; 12(5): 2128–2137
Step 1:
• Educate your users
– Provide them with Standard Operating Procedures
– Sample Handling Procedures
– Standard Digestion Protocols
• Educate yourself and your staff
– Training classes, Workshops, Literature, Books
• learn statistics (CV, ANOVA, Blocking, T-test)
– Journal Clubs (discuss good vs. bad research)
Define the Goal of the experiment
- For each project
- Clearly articulate a goal
- Develop methods to measure results
- Outline Sample design
- Get Statistical help at beginning!!!
- Discuss internal and external standards
- Measure and repeat
Simplify
A
B
C
D
Design, Measure, and Repeat
• Design Assays which can Measure the variability in
each step of your process
• Measure this variability in a controlled experiment
• Replicates are essential (technical, biological)
Example
Measuring Between Animal, Cage, Prep Date, and Condition
cage rat ID tissue frozen or unfrozen prep-date fractions
A
1
half cortex unfrozen Day 1 Subfraction 1 and Subfraction 2
half cortex frozen Day 1 Subfraction 1 and Subfraction 2
2
half cortex unfrozen Day 1 Subfraction 1 and Subfraction 2
half cortex frozen Day 1 Subfraction 1 and Subfraction 2
B
3
half cortex unfrozen Day 2 Subfraction 1 and Subfraction 2
half cortex frozen Day 2 Subfraction 1 and Subfraction 2
4
half cortex unfrozen Day 2 Subfraction 1 and Subfraction 2
half cortex frozen Day 2 Subfraction 1 and Subfraction 2
C
5
half cortex frozen Day 2 Subfraction 1 and Subfraction 2
half cortex frozen Day 3 Subfraction 1 and Subfraction 2
6
half cortex frozen Day 2 Subfraction 1 and Subfraction 2
half cortex frozen Day 3 Subfraction 1 and Subfraction 2
D
7
half cortex frozen Day 2 Subfraction 1 and Subfraction 2
half cortex frozen Day 3 Subfraction 1 and Subfraction 2
8
half cortex frozen Day 2 Subfraction 1 and Subfraction 2
half cortex frozen Day 3 Subfraction 1 and Subfraction 2
PCA plot for Subfraction 1 and Subfraction 2
SWATH data from 1700 proteins
Red – Day 1, Green – Day 2, Blue – Day 3
circles: Cage A, squares: Cage B, triangles: Cage C
Solid(Filled) Rat 1,3,5, Open (No fill) Rat 2,4,6
Subfraction 2Subfraction 1
SubFraction 1 Subfraction 2
red: day1
green: day2
blue: day3
Effect of preparation conditions on ALL proteins
Clustering for Subfraction 1 and Subfraction 2
SWATH data from 1700 proteins
Day1
Day2
Day 0
PCA on Subfraction 1 (between animals, cages, or prep-dates)
red: day1
green: day2
blue: day3
Comparison of Subfraction 1 fractions between prep-dates
red: day1
green: day2
blue: day3
PCA on Subfraction 2 between prep-dates
Four steps
1. Educate
1. Define Goal
2. Simplify
3. Design, Measure
and Repeat
A B C

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Colangelo asms workshop_061714

  • 1. Controlling and Measuring Variation in Sample Preparation and Data Analysis in a Core Facility Environment Christopher Colangelo Director of Protein Profiling MS & Proteomics Resource Yale University June 17, 2014 Analytical Lab Managers Interest Group ASMS – Baltimore, MD
  • 2. Sources of Technical Variability in Quantitative LC-MS Proteomics: Human Brain Tissue Sample Analysis Piehowski et. al. J. Proteome Res. 2013; 12(5): 2128–2137
  • 3. Step 1: • Educate your users – Provide them with Standard Operating Procedures – Sample Handling Procedures – Standard Digestion Protocols • Educate yourself and your staff – Training classes, Workshops, Literature, Books • learn statistics (CV, ANOVA, Blocking, T-test) – Journal Clubs (discuss good vs. bad research)
  • 4. Define the Goal of the experiment - For each project - Clearly articulate a goal - Develop methods to measure results - Outline Sample design - Get Statistical help at beginning!!! - Discuss internal and external standards - Measure and repeat
  • 6. Design, Measure, and Repeat • Design Assays which can Measure the variability in each step of your process • Measure this variability in a controlled experiment • Replicates are essential (technical, biological)
  • 7. Example Measuring Between Animal, Cage, Prep Date, and Condition cage rat ID tissue frozen or unfrozen prep-date fractions A 1 half cortex unfrozen Day 1 Subfraction 1 and Subfraction 2 half cortex frozen Day 1 Subfraction 1 and Subfraction 2 2 half cortex unfrozen Day 1 Subfraction 1 and Subfraction 2 half cortex frozen Day 1 Subfraction 1 and Subfraction 2 B 3 half cortex unfrozen Day 2 Subfraction 1 and Subfraction 2 half cortex frozen Day 2 Subfraction 1 and Subfraction 2 4 half cortex unfrozen Day 2 Subfraction 1 and Subfraction 2 half cortex frozen Day 2 Subfraction 1 and Subfraction 2 C 5 half cortex frozen Day 2 Subfraction 1 and Subfraction 2 half cortex frozen Day 3 Subfraction 1 and Subfraction 2 6 half cortex frozen Day 2 Subfraction 1 and Subfraction 2 half cortex frozen Day 3 Subfraction 1 and Subfraction 2 D 7 half cortex frozen Day 2 Subfraction 1 and Subfraction 2 half cortex frozen Day 3 Subfraction 1 and Subfraction 2 8 half cortex frozen Day 2 Subfraction 1 and Subfraction 2 half cortex frozen Day 3 Subfraction 1 and Subfraction 2
  • 8. PCA plot for Subfraction 1 and Subfraction 2 SWATH data from 1700 proteins Red – Day 1, Green – Day 2, Blue – Day 3 circles: Cage A, squares: Cage B, triangles: Cage C Solid(Filled) Rat 1,3,5, Open (No fill) Rat 2,4,6 Subfraction 2Subfraction 1
  • 9. SubFraction 1 Subfraction 2 red: day1 green: day2 blue: day3 Effect of preparation conditions on ALL proteins Clustering for Subfraction 1 and Subfraction 2 SWATH data from 1700 proteins
  • 10. Day1 Day2 Day 0 PCA on Subfraction 1 (between animals, cages, or prep-dates)
  • 11. red: day1 green: day2 blue: day3 Comparison of Subfraction 1 fractions between prep-dates
  • 12. red: day1 green: day2 blue: day3 PCA on Subfraction 2 between prep-dates
  • 13. Four steps 1. Educate 1. Define Goal 2. Simplify 3. Design, Measure and Repeat A B C

Notas do Editor

  1. I want to thank Kieran for inviting me to come to Pifzer today. I look forward to meeting with entire CCIE team throughout the day Today my presentation will be highlighting some of the more recent proteomic collaborative research projects.