metaMix v0.3


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Bayesian Mixture Analysis for Metagenomic Community Profiling

Resolves complex metagenomic mixtures by analysing deep sequencing data, using a mixture model based approach. The use of parallel Monte Carlo Markov chains for the exploration of the species space enables the identification of the set of species more likely to contribute to the mixture.

Functions in metaMix

Name Description
step2 Example output of for use in the vignette/examples
bayes.model.aver Bayesian Model Averaging
generative.prob Compute generative probabilities from BLAST output
step1 Example output of generative.prob() for use in the vignette/examples Reduce the space of potential species by fitting the mixture model with all potential species as categories
parallel.temper Parallel Tempering MCMC
step3 Example output of parallel.temper() for use in the vignette/examples
parallel.temper.nucl Parallel Tempering MCMC
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Vignettes of metaMix

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VignetteBuilder knitr
License GPL-3
LazyData true
SystemRequirements Open MPI (>=1.4.3)
RoxygenNote 6.1.1
Encoding UTF-8
NeedsCompilation yes
Packaged 2019-02-07 15:41:40 UTC; sophia
Repository CRAN
Date/Publication 2019-02-11 16:20:03 UTC

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