A Bayesian compositional estimator for microbial taxonomy based on biomarkers

TY - JOUR

T1 - A Bayesian compositional estimator for microbial taxonomy based on biomarkers

AU - Van den Meersche, K.

AU - Middelburg, J.J.

AU - Soetaert, K.E.R.

N1 - Reporting year: 2008 Metis note: 4279;CEME; ES; file:///C:/pdfs/PDFS2008/VandenMeersche_ea_4279.pdf

PY - 2008

Y1 - 2008

N2 - Determination of microbial taxonomy based on lipid or pigment spectra requires use of a compositional estimator. We present a new approach based on Bayesian inference and an implementation in the open software platform R. The Bayesian Compositional Estimator (BCE) aims not only to obtain a maximum likelihood solution, but also to provide a complete estimate of the taxonomic composition, including probability distributions and dependencies between estimated values. BCE results are compared with those obtained with CHEMTAX. The BCE has not only a similar accuracy, but also extracts more information from the data, the most obvious being standard deviation and covariance estimates

AB - Determination of microbial taxonomy based on lipid or pigment spectra requires use of a compositional estimator. We present a new approach based on Bayesian inference and an implementation in the open software platform R. The Bayesian Compositional Estimator (BCE) aims not only to obtain a maximum likelihood solution, but also to provide a complete estimate of the taxonomic composition, including probability distributions and dependencies between estimated values. BCE results are compared with those obtained with CHEMTAX. The BCE has not only a similar accuracy, but also extracts more information from the data, the most obvious being standard deviation and covariance estimates

U2 - 10.4319/lom.2008.6.190

DO - 10.4319/lom.2008.6.190

M3 - Article

VL - 6

SP - 190

EP - 199

JO - Limnology and Oceanography: Methods

JF - Limnology and Oceanography: Methods

SN - 1541-5856

ER -