Quality Control in SELDI-TOF Mass Spectrometry
Author Information
Author(s): Hong Huixiao, Dragan Yvonne, Epstein Joshua, Teitel Candee, Chen Bangzheng, Xie Qian, Fang Hong, Shi Leming, Perkins Roger, Tong Weida
Primary Institution: Division of Bioinformatics, Z-Tech at FDA's National Center for Toxicological Research
Hypothesis
Can a correlation matrix effectively identify low quality spectra in SELDI-TOF mass spectrometry data?
Conclusion
The study confirms that systematic variability in SELDI-TOF mass spectrometry does not exist, and a correlation matrix is an effective tool for identifying low quality spectra.
Supporting Evidence
- The correlation matrix approach was applied to the liver cancer and toxicity study and the myeloma-associated lytic bone disease study.
- Reproducibility of SELDI experiments was demonstrated with coefficients of variation less than 20%.
- No systematic variability was found across plates, chips, or spot locations.
- Low quality spectra were identified and removed to ensure reliable biomarker identification.
Takeaway
This study shows how scientists can check the quality of data from a special type of mass spectrometry to make sure they are using good information to find disease markers.
Methodology
The study used a correlation matrix to assess the quality of SELDI-TOF mass spectrometry data from quality control samples.
Limitations
The study does not address the potential sources of variability in the SELDI process itself.
Participant Demographics
The study included plasma samples from two individuals (one male, one female) and sera from 64 newly diagnosed myeloma patients.
Digital Object Identifier (DOI)
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