This repository contains scripts and files to run the bioinformatic analysis of whole genome sequencing of viruses using Illumina or Oxford Nanopore Technologies platforms.
git clone --recursive https://github.com/khourious/vigeas.git && cd vigeas
chmod 700 -R INSTALL_Unix scripts
bash INSTALL_Unix
POD5 is the current raw data format generated by ONT sequencing devices. For basecalling and demultiplexing, we provide an IPython notebook that utilizes GPU acceleration for faster processing, which can be used as an alternative if you don't have access to local GPU resources.
For older raw FAST5 data, ONT provides a tool to convert FAST5 files to POD5: https://pod5.nanoporetech.com/
This workflow expects demultiplexed data in BAM format. Ensure your input folder contains BAM files named with their respective barcodes (e.g., barcode01.bam
, barcode02.bam
). If your data is in FASTQ format, use the following conversion:
samtools import -0 input.fastq.gz -o output.bam
Prepare a sample sheet in CSV format with the following columns:
- sample_id: sample identifier
- barcode: barcode ID in BC format (e.g.,
BC01
,BC02
) - primer_scheme: primer scheme name including version (e.g.,
ChikAsianECSA_V1
)
Example:
976530,BC01,ARTIC_V4
985322,BC02,ZikaAsian_V2
Available primer schemes in this workflow can be found at: primer_schemes/README.md
Usage: vigeas <command> or <miscellaneous>
Commands:
ill For Illumina Sequencing [*.fastQ data]
ont For ONT Sequencing [*.pod5 data]
Miscellaneous:
clr3 List supported Clair3 models
makedb Create a BLAST database in this workflow -- for <vigeas ill -x hyb>
panels List available enrichment panels in this workflow -- for <vigeas ill -x hyb>
primers List available primer schemes in this workflow -- for <vigeas ill -x amp> and <vigeas ont -x bda>
update Update conda/mamba dependencies
version Show last update information
Thanks to:
- Ricardo Khouri (Rkhour0) for mentorship and discussions on improving in the
-x amp
and-x ill
workflows. - Verity Hill (ViralVerity) for her collaborative troubleshooting regarding low-coverage sequencing issues, primer trimming, and bioinformatic pipeline optimizations for DENV, ZIKV, and CHIKV data.