Name
Abstract | ||
|---|---|---|
Mass spectrometry data are subjected to considerable noise. Good noise models are required for proper detection and quantification of peptides. We have characterized noise in both quadrupole time-of-flight (Q-TOF) and ion trap data, and have constructed models for the noise.We find that the noise in Q-TOF data from Applied Biosystems QSTAR fits well to a combination of multinomial and Poisson model with detector dead-time correction. In comparison, ion trap noise from Agilent MSD-Trap-SL is larger than the Q-TOF noise and is proportional to Poisson noise. We then demonstrate that the noise model can be used to improve deisotoping for peptide detection, by estimating appropriate cutoffs of the goodness of fit parameter at prescribed error rates. The noise models also have implications in noise reduction, retention time alignment and significance testing for biomarker discovery. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1093/bioinformatics/btn078 | Bioinformatics |
Keywords | Field | DocType |
mass spectrometry,noise model,ion trap data,good noise model,q-tof data,poisson noise,noise reduction,considerable noise,mass spectrometry data,ion trap noise,q-tof noise,time of flight,error rate,ion trap,poisson model,goodness of fit,retention time | Noise reduction,Data mining,Ion trap,Liquid chromatography–mass spectrometry,Computer science,Multinomial distribution,Algorithm,Mass spectrometry,Statistics,Shot noise,Detector,Goodness of fit | Journal |
Volume | Issue | ISSN |
24 | 8 | 1367-4811 |
Citations | PageRank | References |
8 | 0.91 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peicheng Du | 1 | 16 | 2.14 |
| Gustavo Stolovitzky | 2 | 738 | 51.84 |
| Peter Horvatovich | 3 | 10 | 1.73 |
| Rainer Bischoff | 4 | 206 | 22.10 |
| Jihyeon Lim | 5 | 8 | 0.91 |
| F. Suits | 6 | 201 | 29.82 |