- recipe bioconductor-sparsedossa
Sparse Data Observations for Simulating Synthetic Abundance
- Homepage:
https://bioconductor.org/packages/3.17/bioc/html/sparseDOSSA.html
- License:
MIT + file LICENSE
- Recipe:
The package is to provide a model based Bayesian method to characterize and simulate microbiome data. sparseDOSSA's model captures the marginal distribution of each microbial feature as a truncated, zero-inflated log-normal distribution, with parameters distributed as a parent log-normal distribution. The model can be effectively fit to reference microbial datasets in order to parameterize their microbes and communities, or to simulate synthetic datasets of similar population structure. Most importantly, it allows users to include both known feature-feature and feature-metadata correlation structures and thus provides a gold standard to enable benchmarking of statistical methods for metagenomic data analysis.
- package bioconductor-sparsedossa¶
- Versions:
1.24.0-0,1.22.0-0,1.18.0-0,1.16.0-0,1.14.0-1,1.14.0-0,1.12.0-0,1.10.0-0,1.8.0-1,1.24.0-0,1.22.0-0,1.18.0-0,1.16.0-0,1.14.0-1,1.14.0-0,1.12.0-0,1.10.0-0,1.8.0-1,1.8.0-0,1.6.1-0- Depends:
on r-base
>=4.3,<4.4.0a0on r-mass
on r-mcmcpack
on r-optparse
on r-tmvtnorm
>=1.4.10
- Additional platforms:
Installation¶
You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).
Pixi¶
With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:
pixi global install bioconductor-sparsedossa
to add into an existing workspace instead, run:
pixi add bioconductor-sparsedossa
In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:
pixi workspace channel add conda-forge
pixi workspace channel add bioconda
Conda¶
With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:
conda install bioconductor-sparsedossa
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-sparsedossa
with envname being the name of the desired environment.
Container¶
Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:
docker pull quay.io/biocontainers/bioconductor-sparsedossa:<tag>
(see bioconductor-sparsedossa/tags for valid values for <tag>).
Integrated deployment¶
Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-sparsedossa/README.html)
