Designing quantitative proteomics experiments
This presentation demonstrates what happens when you design your experiments well, and what happens when you don't! It shows how a little time spent planning before you start collecting your samples delivers reliable and reproducible results.
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Dr. Natasha Karp, Cambridge Centre for Proteomics
Analysis of Large-Scale Data Sets
This presentation takes you through some important details necessary to design high quality proteomics experiments. It includes a section that clearly demonstrates the trade off between minimising the cost of running proteomics experiments and maximising chances of reliably distinguishing a real biological effect.
Click here to view this presentation (PDF – 1MB)
Massimiliano Gentile, Biomedicum Bioinformatics Unit, Helsinki, Finland
Statistical strategies for avoiding false discoveries in metabolomics and related experiments
This is a paper from 2006 that can take you into real depth of how to apply statistics to reduce the potential of false discoveries. It comes from the related field of metabolomics research but has some application for proteomics and shares commonality on how challenging it can be do to "good experiments" in these fields. Read the full paper
David Broadhurst, Senior Postdotoral
Reseacher at Cork University Maternity Hospital
Prof. Douglas
Kell, Chief Executive of the Biotechnology and Biological Sciences
Research Council
Experimental Design for Plasma Biomarker Discovery using iTRAQ
This publication investigates aspects of experimental design for large studies that require analysis of multiple sample sets using iTRAQ reagents for sample multiplexing and quantitation. It examines the influence of different reference samples, such as pooled samples or individual samples on calculating quantitative ratios. The findings are discussed in the context of optimizing iTRAQ experimental design for robust plasma-based biomarker discovery.
Professor Mark S. Baker, Director, Australian Proteome Analysis Facility (APAF@MQ)
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