atrigila/nf-core-saliva

Introduction

nf-core/saliva is a bioinformatics analysis pipeline to process VCFs obtained from saliva samples.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.

Pipeline summary

1. Download VCFs from your projects at Gencove (FastQC)
2. Filter VCFs by your desired RSIDs (VCFTools)
3. Transform your VCFs into PLINK binary files (PLINK)
4. Store your data in a MongoDB (MongoDB)
5. Store your data in a TileDB (TileDB)

Quick Start

1. Install Nextflow (>=21.10.3)

2. Install any of Docker, Singularity (you can follow this tutorial), Podman, Shifter or Charliecloud for full pipeline reproducibility (you can use Conda both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see docs).

3. Download the pipeline and test it on a minimal dataset with a single command:

   nextflow run nf-core/saliva -profile test,YOURPROFILE --outdir <OUTDIR>

   You will need to also add specific flags regarding your API KEYs and URIs of your desired datastores. Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (YOURPROFILE in the example command above). You can chain multiple config profiles in a comma-separated string.

   • The pipeline comes with config profiles called docker, singularity, podman, shifter, charliecloud and conda which instruct the pipeline to use the named tool for software management. For example, -profile test,docker.
   • Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.
   • If you are using singularity, please use the nf-core download command to download images first, before running the pipeline. Setting the NXF_SINGULARITY_CACHEDIR or singularity.cacheDir Nextflow options enables you to store and re-use the images from a central location for future pipeline runs.
   • If you are using conda, it is highly recommended to use the NXF_CONDA_CACHEDIR or conda.cacheDir settings to store the environments in a central location for future pipeline runs.

4. Start running your own analysis!

   nextflow run nf-core/saliva --projectid your-project-id --apikey your-api-key --url_mongo your-mongo-db --tiledbvcf_uri your-tdb-uri --rsid_file rsidfile.txt --outdir <OUTDIR> --genome GRCh37 -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>

Credits

nf-core/saliva was originally written by Anabella.

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.

nf-core-saliva's Issues

Module PLINK_VCF does not run

Description of the bug

When running a test of the sample, the step of PLINK_VCF does not work.

Command used and terminal output

nextflow run nf-core-saliva/ --outdir test_dir --input_vcf sampleVCF.vcf.gz -profile test,docker --rsid_file SAMPLE_RSID.txt

Relevant files

nextflow.log

System information

• Nextflow version: version 22.04.3
  

• Hardware: Desktop
  

• Executor: local
  

• Container engine:  Docker
  

• OS: Linux