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https://github.com/tare/GPMicrobiome
A novel probabilistic approach to explicitly model overdispersion and sampling zeros in 16S rRNA sequencing data by considering the temporal correlation between nearby time points using Gaussian Processes
https://github.com/tare/GPMicrobiome
Last synced: 11 days ago
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A novel probabilistic approach to explicitly model overdispersion and sampling zeros in 16S rRNA sequencing data by considering the temporal correlation between nearby time points using Gaussian Processes
- Host: GitHub
- URL: https://github.com/tare/GPMicrobiome
- Owner: tare
- License: mit
- Created: 2016-04-22T13:53:41.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2024-10-22T00:05:13.000Z (19 days ago)
- Last Synced: 2024-10-22T12:45:24.238Z (18 days ago)
- Language: Python
- Homepage:
- Size: 597 KB
- Stars: 7
- Watchers: 2
- Forks: 4
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-rm-omics - **TGP-CODA** - Äijö - [Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing](https://doi.org/10.1093/bioinformatics/btx549) (Software packages and methods / Stochastic/Probabilistic Modeling)
README
# GPMicrobiome
Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing.
## Installation
### PyPI
```console
$ pip install gpmicrobiome
```
### GitHub
Install the version from the main branch as follows
```console
$ pip install git+https://github.com/tare/GPMicrobiome.git
```
## Usage
Please see [this](examples/basic_usage.ipynb) tutorial.