QuasiFlow: A Nextflow Pipeline for Analysis of NGS-based HIV-1 Drug Resistance Data
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Date
2022
Authors
Ssekagiri, Alfred
Jjingo, Daudi
Lujumba, Ibra
Bbosa, Nicholas
Bugembe, Daniel L.
Kateete, David P.
Kaleebu, Pontiano
Ssemwanga, Deogratius
Journal Title
Journal ISSN
Volume Title
Publisher
Bioinformatics advances
Abstract
Next-generation sequencing (NGS) enables reliable detection of resistance mutations in minority variants
of human immunodeficiency virus type 1 (HIV-1). There is paucity of evidence for the association of minority resistance to treatment failure, and this requires evaluation. However, the tools for analyzing HIV-1 drug resistance (HIVDR) testing data are mostly web-based which requires uploading data to webservers. This is a challenge for laboratories with internet connectivity issues and instances with restricted data transfer across networks. We present
QuasiFlow, a pipeline for reproducible analysis of NGS-based HIVDR testing data across different computing environments. Since QuasiFlow entirely depends on command-line tools and a local copy of the reference database, it eliminates challenges associated with uploading HIV-1 NGS data onto webservers. The pipeline takes raw sequence reads in FASTQ format as input and generates a user-friendly report in PDF/HTML format. The drug resistance scores obtained using QuasiFlow were 100% and 99.12% identical to those obtained using web-based HIVdb program and HyDRA web respectively at a mutation detection threshold of 20%.
Description
Keywords
Mutations, Human immunodeficiency virus type 1, Data
Citation
Ssekagiri, A., Jjingo, D., Lujumba, I., Bbosa, N., Bugembe, D. L., Kateete, D. P., ... & Ssemwanga, D. (2022). QuasiFlow: a Nextflow pipeline for analysis of NGS-based HIV-1 drug resistance data. Bioinformatics advances, 2(1), vbac089.https://doi.org/10.1093/bioadv/vbac089