Abstract
Proteomic expression patterns derived from mass spectrometry have been put forward as potential biomarkers for the early diagnosis of cancer and other diseases. This approach has generated much excitement and has led to a large number of new experiments and vast amounts of new data. The data, derived at great expense, can have very little value if careful attention is not paid to the experimental design and analysis. Using examples from surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) and matrix-assisted laser desorption-ionisation/time-of-flight (MALDI-TOF) experiments, we describe several experimental design issues that can corrupt a dataset. Fortunately, the problems we identify can be avoided if attention is paid to potential sources of bias before the experiment is run. With an appropriate experimental design, proteomics technology can be a useful tool for discovering important information relating protein expression to disease.
Original language | English (US) |
---|---|
Pages (from-to) | 322-331 |
Number of pages | 10 |
Journal | Briefings in Functional Genomics and Proteomics |
Volume | 3 |
Issue number | 4 |
DOIs | |
State | Published - Feb 2005 |
Externally published | Yes |
Keywords
- Calibration
- Data preprocessing
- Follow-up studies
- Proteomic mass spectrometry
- Randomised run order
- Validation
ASJC Scopus subject areas
- Biochemistry
- Molecular Biology
- Genetics