Aquascope

This project is a successor to the C-WAP pipeline and is intended to process SARS-CoV-2 wastewater samples to determine relative variant abundance.

⚠️Warning⚠️

The results generated by this pipeline are not CLIA certified and should not be considered diagnostic.

Introduction

CDCgov/aquascope is a bioinformatics best-practice pipeline for early detection of SARS-COV variants of concern, sequenced throughshotgun metagenomic sequencing, from wastewater.

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.

Pipeline summary

1. Read QC: FastQC
2. Trimming reads: Fastp
3. Aligning short reads: Minimap2
4. Freyja Variant classification: Freyja
5. Present QC for raw reads: MultiQC

Quick Start

1. Install Nextflow (>=21.04.0)

2. Install any of Docker, Singularity, Podman, Shifter or Charliecloud for full pipeline reproducibility (please only use Conda as a last resort; see docs)

3. Prepare the assets/samplesheet.csv

   • Use the assets/test_highcoverage_samplesheet.csv as an example

   • Create custom sample sheets using the fastq_dir_to_samplesheet.py script

      Usage: 
      	fastq_dir_to_samplesheet.py \
      	/absolute/path/to/fastq/dir \
      	-st <forward/reverse/unstranded> \
      	samplesheetName.csv 
     

     i. FASTQ files must be paired end, following _R1, _R2 naming convention.

     ii. Strandedness must be known or "unstranded". NOTE: DNASeq is by default unstranded, while RNASeq is usually stranded

4. Prepare the configuration files A. nextflow.config is prepared with default parameters, update as needed B. test.config is prepared with default parameters, update as needed

5. Run the pipeline profile

   nextflow run \
     main.nf \
     -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> \
   	  -entry <QUALITY_ALIGN, FREYJA_ONLY, AQUASCOPE>
   

   A. The -profile test will run the test parameters and samples only for test data - test_illumina: Runs Illumina data - test_ont: Runs ONT data - test_bams: Runs BAM data B. 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. NOTE: CDC users can only use singularity on SciComp resources. C. If you are using singularity then the pipeline will auto-detect this and attempt to download the Singularity images directly. If you are persistently observing issues downloading Singularity images directly due to timeout or network issues then please use the --singularity_pull_docker_container parameter to pull and convert the Docker image instead. D. 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.

Documentation

For more detailed documentation, please visit our user-guides.

Contributions and Support

Aquascope was largely developed by OAMD's SciComp Team, with inputs from NWSS and the DCIPHER Team at Palantir. Detailed contributions can be found in our user-guides.

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.