https://github.com/solida-core/dica
https://github.com/solida-core/dica
Last synced: 8 months ago
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- Host: GitHub
- URL: https://github.com/solida-core/dica
- Owner: solida-core
- License: gpl-3.0
- Created: 2022-07-19T10:03:53.000Z (almost 4 years ago)
- Default Branch: master
- Last Pushed: 2022-07-20T07:42:23.000Z (almost 4 years ago)
- Last Synced: 2025-05-18T12:37:08.308Z (about 1 year ago)
- Language: Python
- Size: 25.4 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Snakemake workflow: DiCa
[](https://snakemake.bitbucket.io)
This workflow performs mapping and variant calling following GATK Best Practices for Germline Variant Discovery.
DiCA is part of the Snakemake-based pipelines collection [solida-core](https://github.com/solida-core) developed and manteined at [CRS4](https://www.crs4.it).
## Authors
* Matteo Massidda (@massiddaMT)
* Rossano Atzeni (@ratzeni)
## Usage
The usage of this workflow is described in the [Snakemake Workflow Catalog](https://snakemake.github.io/snakemake-workflow-catalog?usage=solida-core/dica).
If you use this workflow in a paper, don't forget to give credits to the authors by citing the URL of this (original) repository and its DOI (see above).
## INSTRUCTIONS
Create a virtual environment with the command:
```commandline
mamba create -c bioconda -c conda-forge --name snakemake snakemake=6.15 snakedeploy
```
and activate it:
```commandline
conda activate snakemake
```
We get some public data to test the pipeline. You can directly clone in this folder from github, just type:
```commandline
git clone https://github.com/solida-core/test-data-DNA.git
```
You can then perform the pipeline deploy defining a directory `my_dest_dir` for analysis output and a pipeline tag for a specific version:
```bash
snakedeploy deploy-workflow https://github.com/solida-core/dica
my_desd_dir
--tag XXXX
```
To run the pipeline, go inside the deployed pipeline folder and use the command:
```bash
snakemake --use-conda -p --cores all
```
You can generate analysis report with the command:
```bash
snakemake --report report.zip --cores all
```