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https://github.com/achillesrasquinha/16smart
16s rRNA Sequencing Meta-analysis Reproducibility Tool (using mothur).
https://github.com/achillesrasquinha/16smart
16s-rrna bioinformatics meta-analysis mothur python reproducible-research sequencing
Last synced: 5 days ago
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16s rRNA Sequencing Meta-analysis Reproducibility Tool (using mothur).
- Host: GitHub
- URL: https://github.com/achillesrasquinha/16smart
- Owner: achillesrasquinha
- License: mit
- Created: 2021-10-09T17:22:20.000Z (about 3 years ago)
- Default Branch: develop
- Last Pushed: 2022-11-26T22:05:52.000Z (almost 2 years ago)
- Last Synced: 2023-03-02T07:31:52.878Z (over 1 year ago)
- Topics: 16s-rrna, bioinformatics, meta-analysis, mothur, python, reproducible-research, sequencing
- Language: Python
- Homepage:
- Size: 2.77 MB
- Stars: 7
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
16SMaRT
16s rRNA Sequencing Meta-analysis Reconstruction Tool.
**16SMaRT** is a bioinformatics analysis pipeline for 16s rRNA gene sequencing data. 16SMaRT is a "one-click" solution towards performing microbial community analysis of amplicon sequencing data. 16SMaRT aims to be your go-to solution for your next microbiome/metagenomics project. The primary objective of 16SMaRT analysis is to determine what genes are present and in what proportions in comparison across a range of samples. It currently supports single-end or paired-end [Illumina](https://www.illumina.com/) MiSeq data.
16SMaRT is written in Python using [boilpy's](https://github.com/achillesrasquinha/boilpy) data-pipeline boilerplate.
16SMaRT is built on top of a considerable amount of dependencies and hence, the recommended way to install it is by using [docker](#using-docker) thus making installation in "one-click" and perfectly reproducible results. 16SMaRT is built with considering maximizing computation resources in mind thereby making it blazingly fast even on a local machine for a decent amount of samples. For a large number of studies, it is recommended to run 16SMaRT on a High-Performance Computing system using [singularity](#running-on-hpc-systems-using-singularity).
## Table of Contents
* [Features](#features)
* [Quick Start](#quick-start)
* [Usage](#usage)
* [Support](#support)
* [Citation](#citation)
* [License](#license)
## Features
* Supports single-end and paired-end [Illumina](https://www.illumina.com/) data.
* Quality Control using [FASTQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and [MultiQC](https://multiqc.info/).
* Trimming using [mothur](https://mothur.org).
* Analysis using [phyloseq](https://joey711.github.io/phyloseq/).
* Multi-Processing.
* [Docker](https://www.docker.com/) + [Singularity](https://singularity.hpcng.org/) support.
## Quick Start
### Using [Docker](https://www.docker.com/)
First, install docker onto your system (can be followed via [docker's documentation](https://docs.docker.com/engine/install)).
Then, you can run simply run 16SMaRT by the following command:
```
docker run \
--rm -it \
-v ":/data" \
-v ":/root/.config/s3mart \
-v ":/work \
ghcr.io/achillesrasquinha/s3mart \
bpyutils --run-ml s3mart -p "data_dir=/data" --verbose
```
where `` is the path to your host machine to store pipeline data and `` is the path to store 16SMaRT configuration and intermediate data. `` is a workspace directory for you to store your files that can be used by 16SMaRT (e.g. input files).
### Running on HPC systems using [Singularity](https://singularity.hpcng.org/)
Singularity is the most widely used container system for HPC (High-Performance Computing) systems. In order to run your analysis on an HPC system, simply run the following command.
```
singularity run \
--home $HOME \
--cleanenv \
-B :/data \
-B :/root/.config/s3mart \
-B :/work \
oras://ghcr.io/achillesrasquinha/s3mart:singularity \
bpyutils --run-ml s3mart -p "data_dir=/data" --verbose
```
## Usage
### Basic Usage
* [**`input`**]()
*Path to input CSV file, data directory of FASTQ files, URL to CSV file.*
* [**`fastqc`**]()
*Run FASTQC after downloading SRAs.* (boolean, default - `True`)
* [**`multiqc`**]()
*Run MultiQC after performing FASTQC.* (boolean, default - `True`)
Check out the [docs](docs/source) page to understand how to use this pipeline.
## Support
Have any queries? Post an issue on the [GitHub Issue Tracker](https://github.com/achillesrasquinha/16SMaRT/issues).
## Citation
If you use this software in your work, please cite it using the following:
> Furbeck, R., & Rasquinha, A. (2021). 16SMaRT - 16s rRNA Sequencing Meta-analysis Reconstruction Tool. (Version 0.1.0) [Computer software]. [https://github.com/achillesrasquinha/16SMaRT](https://github.com/achillesrasquinha/16SMaRT)
A comprehensive list of references for the tools used is listed [here](REFERENCES.md).
## License
This repository has been released under the [MIT License](LICENSE).
---