https://github.com/gmauro/dima
https://github.com/gmauro/dima
Last synced: 2 months ago
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- Host: GitHub
- URL: https://github.com/gmauro/dima
- Owner: gmauro
- Created: 2017-10-10T09:11:21.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-04-22T17:14:38.000Z (about 7 years ago)
- Last Synced: 2025-02-03T11:14:28.936Z (4 months ago)
- Language: Python
- Size: 75.2 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# DiMA
Snakemake pipeline to map DNA datasets to a given reference genome using [BWA
MEM](https://github.com/lh3/bwa/) and [Samtools](http://www.htslib.org/).
Input datsets are fastq files gzipped. Can be organized in
multiple
units for each sample or also only one unit per sample; in the last case, file will be
copied.
Output can be produced in BAM or CRAM (_default_) format.
## Requirements
The pipeline's requirements are specified into the _environment.yml_ file and
packages dependency are resolved using [Conda](https://conda.io/miniconda.html).
## Usage
### Manual deployment (a.k.a. hard way)
Clone the repository and cd in it
```bash
git clone https://bitbucket.org/biopipelines/dima
cd dima
```
Edit the configuration file and the Snakefile to match your environment
```
nano config.test.data.json
nano Snakefile
```
Create conda environment
```
conda env create -n dima --file environment.yml
```
then activate it
```
source activate dima
```
Launch Snakemake
```
snakemake --use-conda --configfile config.test.data.json
```
### Automatic deployment (a.k.a. easy way)
Use [Solida](https://bitbucket.org/biopipelines/solida).
### Output
Default output of the pipeline in CRAM format, but can changed easily in BAM
editing the Snakefile (look for OUTPUT_FORMAT variable)
## Contributing
Contributions from everyone and anyone are welcome.
Fork this repository, make your changes and create a Pull Request.
Then one of the maintainers will review your changes.
When all comments have been addressed and all tests pass, your changes will
be merged.