Author: Sofia Morfopoulou; Vincent Plagnol
Title: Bayesian mixture analysis for metagenomic community profiling. Document date: 2014_7_25
ID: 058r9486_73
Snippet: However the goal of this work is to deliver results in a clinical setting within an actionable time-frame. We wish to speed up the computation without compromising the accuracy and the sensitivity of the results. For that reason, we use a point estimate of the marginal likelihood by means of the Expectation-Maximization (EM) algorithm. The different approaches were used on the benchmark dataset. The resulting taxonomic assignment as well as the s.....
Document: However the goal of this work is to deliver results in a clinical setting within an actionable time-frame. We wish to speed up the computation without compromising the accuracy and the sensitivity of the results. For that reason, we use a point estimate of the marginal likelihood by means of the Expectation-Maximization (EM) algorithm. The different approaches were used on the benchmark dataset. The resulting taxonomic assignment as well as the species relative abundance estimates were similar between them, with the EM approach resulting in a 13-fold speed increase (Supplementary Text 1).
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