Premium
Statistical design of experiments as a tool in mass spectrometry
Author(s) -
Riter Leah S.,
Vitek Olga,
Gooding Karen M.,
Hodge Barry D.,
Julian Randall K.
Publication year - 2005
Publication title -
journal of mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 121
eISSN - 1096-9888
pISSN - 1076-5174
DOI - 10.1002/jms.871
Subject(s) - design of experiments , chemistry , mass spectrometry , statistical power , experimental data , statistical analysis , chromatography , biochemical engineering , statistics , engineering , mathematics
This Tutorial is an introduction to statistical design of experiments (DOE) with focus on demonstration of how DOE can be useful to the mass spectrometrist. In contrast with the commonly used one factor at a time approach, DOE methods address the issue of interaction of variables and are generally more efficient. The complex problem of optimizing data‐dependent acquisition parameters in a bottom‐up proteomics LC‐MS/MS analysis is used as an example of the power of the technique. Using DOE, a new data‐dependent method was developed that improved the quantity of confidently identified peptides from rat serum. Copyright © 2005 John Wiley & Sons, Ltd.