TY - GEN
T1 - Bayesian alignment model for LC-MS data
AU - Tsai, Tsung Heng
AU - Tadesse, Mahlet G.
AU - Wang, Yue
AU - Ressom, Habtom W.
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - A Bayesian alignment model (BAM) is proposed for alignment of liquid chromatography-mass spectrometry (LC-MS) data. BAM is composed of two important components: prototype function and mapping function. Estimation of both functions is crucial for the alignment result. We use Markov chain Monte Carlo (MCMC) methods for inference of model parameters. To address the trapping effect of local mode, we propose a block Metropolis-Hastings algorithm that led to better mixing behavior in updating the mapping function coefficients. We applied BAM to both simulated and real LC-MS datasets, and compared its performance with the Bayesian hierarchical curve registration model (BHCR). Performance evaluation on both simulated and real datasets shows satisfactory results in terms of correlation coefficients and ratio of overlapping peak areas.
AB - A Bayesian alignment model (BAM) is proposed for alignment of liquid chromatography-mass spectrometry (LC-MS) data. BAM is composed of two important components: prototype function and mapping function. Estimation of both functions is crucial for the alignment result. We use Markov chain Monte Carlo (MCMC) methods for inference of model parameters. To address the trapping effect of local mode, we propose a block Metropolis-Hastings algorithm that led to better mixing behavior in updating the mapping function coefficients. We applied BAM to both simulated and real LC-MS datasets, and compared its performance with the Bayesian hierarchical curve registration model (BHCR). Performance evaluation on both simulated and real datasets shows satisfactory results in terms of correlation coefficients and ratio of overlapping peak areas.
KW - Bayesian inference
KW - Markov chain Monte Carlo (MCMC)
KW - block Metropolis-Hastings algorithm
KW - liquid chromatography-massspectrometry (LC-MS)
UR - http://www.scopus.com/inward/record.url?scp=84862912301&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862912301&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2011.81
DO - 10.1109/BIBM.2011.81
M3 - Conference contribution
AN - SCOPUS:84862912301
SN - 9780769545745
T3 - Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011
SP - 261
EP - 264
BT - Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011
T2 - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011
Y2 - 12 November 2011 through 15 November 2011
ER -