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 reduce.space() 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.space | 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 | |
| No Results! | ||
Vignettes of metaMix
| Name | ||
| guide.Rnw | ||
| guide.Rnw.bck | ||
| No Results! | ||
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Details
| 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 |
| imports | data.table (>= 1.9.2) , ggplot2 , gtools , Matrix , Rmpi |
| suggests | knitr |
| depends | R (>= 3.2) |
| Contributors | Sofia Morfopoulou |
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