What are the Problems with Experiment Design for Quantitative Proteomics and How Do We Get Past Them

Reproducibility is fundamental to advancing science because it enables scientists to build on the work of others. Unfortunately, proteomics is so challenging that reproducibility and quality control steps must be built into experimental design from the start or experiments are almost guaranteed to be unreliable and irreproducible. This is true regardless of the technique employed and is a barrier for translating proteomics discoveries into clinical impact. This talk will introduce the challenges of running proteomics experiments and you will leave having learnt practical steps towards overcoming these challenges. The practical steps presented are based on analogies from the Fixing Proteomics Campaign, which are designed to be memorable and help you share the information with others. They include approaches to answers such questions as: Are you confident you get the same result every time you run a standard on your system? Are you using enough biological replicates to be confident your results will apply to the wider population you are studying? Do you know everything else you need to design and run a conclusive experiment? Will you be able to reliably reproduce and confirm the results you got from your pilot? Will other labs be able to reliably reproduce and confirm your results? Our goal is that after considering these factors, you'll be much more confident that the results you generate will be biological in nature, reproducible by the community as a whole and are not influenced by specific protocols within your lab. This means you can generate results that have much more impact.