INTRODUCTION: Next Generation Sequencing (NGS) technologies enable reliable detection of minority HIV-1 drug-resistant variants (MDRVs). MDRVs have been associated with an increased risk of virological failure in patients on Non-Nucleoside Reverse Transcriptase Inhibitor based regimens. However, the scarcity of computational skills to effectively and expeditiously identify minority HIV-1 drug resistant variants from NGS-based HIV drug resistance (HIVDR) testing data remains a challenge in resource-limited settings.

METHODS: The pipeline takes paired-end short reads from Illumina platforms as input. The quality of the reads is checked using FastQC which generates a report for each of the input files. FastQC results are aggregated into a single report with MultiQC. Adapter trimming of the reads is done using trim-galore. As part of the Quasitools pipeline Bowtie2 is used to align reads onto the HIV reference genome HXB2 and HyDRA is used for HIV variant calling. Quasitools outputs filtered FASTQ files, amino acid variant call files, a mixed base consensus sequence in FASTA format, and a drug resistance mutation report (consisting of identified drug resistance mutations and corresponding mutational frequencies) in CSV format. The consensus sequence is parsed to sierra-local for scoring of identified drug resistant mutations. The drug resistance report generated by HyDRA is combined with the JSON file (from sierra local) in the R programming environment to generate a comprehensive drug resistance report. The tools are assembled into an automatic workflow using Nextflow. QuasiFlow is distributed with docker containers for all third-party tools.

CONCLUSION: To this end, we developed QuasiFlow, a portable and scalable pipeline for the reproducible analysis of NGS-based HIVDR testing data. QuasiFlow provides a single platform that can run fully offline (with periodic database update) to expeditiously generate user-friendly HIV-1 drug resistance reports from raw NGS data. This tool will improve reporting times of NGS-based HIVDR testing results, especially for researchers with unreliable internet connectivity and in cases where data transfer to remote servers is restricted.