FL BPHL's SARS-CoV-2 (SC2) analysis pipeline for Illumina paired-end, whole-genome tiled-amplicon data enriched from environmental metagenomic samples (e.g., wastewater).
FLAQ-SC2-Meta was developed to analyze Illumina paired-end, whole-genome tiled-amplicon data (i.e., ARTIC protocol) from wastewater samples. The pipeline generates variant files along with reports including read/mapping quality metrics and estimated Pango lineage abundances. The current version will run only on HiPerGator(HPG) using local Singularity containers for each pipeline process.
- Python3.7-3.10
- Singularity/Apptainer
- Git
Singularity/Apptainer will be loaded as a module during your job execution on HPG using the sbatch job script in this repository.
Git is already installed in your HPG environment upon login.
The default primer in the pipeline is ARTIC-V4.1.bed. If your SARS-CoV-2 data use different ARTIC primer, you need change the line 16 "primers="4.1"" in sbatch_flaq_sc2_meta.sh or sbatch_flaq_sc2_meta_lowdepth.sh. For example, if ARTIC-V5.3.2.bed is used, primers="4.1" should be repalced with primers="5.3.2".
For first-time users of the pipeline, please read the file "Guide_for_installation" before you run the pipeline.
For first time use, clone this repository to a directory in blue on HPG, such as in /blue/bphl-<state>/<user>/repos/bphl-molecular/.
cd /blue/bphl-<state>/<user>/repos/bphl-molecular/
git clone https://github.com/BPHL-Molecular/flaq_sc2_meta.git
For future use, update any changes to your local repository on HPG by navigating to the flaq_sc2_meta repository and pulling any changes.
cd flaq_sc2_meta/
git pull
To run the FLAQ-SC2-Meta pipeline, copy all files from the flaq_sc2_meta local repository to your analysis folder. Make an input directory and copy your fastqs.
mkdir <analysis_dir>
cd <analysis_dir>
cp /blue/bphl-<state>/<user>/repos/bphl-molecular/flaq_sc2_meta/* .
mkdir fastqs_ww/
cp /path/to/fastqs/*.fastq.gz fastqs_ww/
Rename your fastq files to the following format: sample_1.fastq.gz, sample_2.fastq.gz. See below for a helpful command to rename your R1 and R2 files.
cd fastqs_ww/
for i in *_R1_001.fastq.gz; do mv -- "$i" "${i%[PATTERN to REMOVE]}_1.fastq.gz"; done
for i in *_R2_001.fastq.gz; do mv -- "$i" "${i%[PATTERN to REMOVE]}_2.fastq.gz"; done
Edit your sbatch job submission script to include your email to receive an email notification upon job END or FAIL. Replace ENTER EMAIL in #SBATCH --mail-user=ENTER EMAIL with your email address. Make sure there is no space between = and your email address. Edit additional sbatch parameters as needed to run your job succesfully, such as the length of time the job will run.
Submit your job.
sbatch sbatch_flaq_sc2_meta_all.sh
Outputs from each process for each individual sample can be found in a sample-specific subdirectory within the FLAQ-SC2-Meta analysis directory. Report.txt contains the main summary report with read/mapping quality metrics. Additional details can be found in the report outputs from each process such as variant files (.variant.tsv) and Freyja reports.
analysis_dir/
|__ <date>_flaq_run/
|__ report.txt
|__ sample1/
|__ sample2/