Browsing by Author "Ssekagiri, Alfred"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    QuasiFlow: A Nextflow Pipeline for Analysis of NGS-based HIV-1 Drug Resistance Data
    (Bioinformatics advances, 2022) Ssekagiri, Alfred; Jjingo, Daudi; Lujumba, Ibra; Bbosa, Nicholas; Bugembe, Daniel L.; Kateete, David P.; Kaleebu, Pontiano; Ssemwanga, Deogratius
    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%.
  • Thumbnail Image
    Item
    Viruses associated with measles-like illnesses in Uganda
    (Journal of Infection, 2024) Namuwulya, Prossy; Shirin, Ashraf; Marc, Niebel; Ssekagiri, Alfred; Tushabe, Phionah; Kakooza, Proscovia; Lily, Tong; Bukenya, Henry; Hanna, Jerome; Chris, Davis; Birungi, Molly; Turyahabwe, Irene; Mugaga, Arnold; Eliku, James Peter; Aine, Francis; Nakabazzi, Lucy; Nsubuga, Fred; Katushabe, Edson; Kisakye, Annet; Ampeire, Immaculate; Nanteza, Ann; Kaleebu, Pontiano; Bakamutumaho, Barnabas; Nsamba, Peninah; Kazibwe, Anne; Ana, da Silva Filipe; Tweyongyere, Robert; Bwogi, Josephine; Thomson, Emma C.
    Objectives In this study, we investigated the causes of measles-like illnesses (MLI) in the Uganda national surveillance program in order to inform diagnostic assay selection and vaccination strategies. Methods We used metagenomic next-generation sequencing (M-NGS) on the Illumina platform to identify viruses associated with MLI (defined as fever and rash in the presence of either cough, coryza or conjunctivitis) in patient samples that had tested IgM negative for measles between 2010 and 2019. Results Viral genomes were identified in 87/271 (32%) of samples, of which 44/271 (16%) contained 12 known viral pathogens. Expected viruses included rubella, human parvovirus B19, Epstein Barr virus, human herpesvirus 6B, human cytomegalovirus, varicella zoster virus and measles virus (detected within the seronegative window-period of infection) and the blood-borne hepatitis B virus. We also detected Saffold virus, human parvovirus type 4, the human adenovirus C2 and vaccine-associated poliovirus type 1. Conclusions The study highlights the presence of undiagnosed viruses causing MLI in Uganda, including vaccine-preventable illnesses. NGS can be used to monitor common viral infections at a population level, especially in regions where such infections are prevalent, including low and middle income countries to guide vaccination policy and optimize diagnostic assays.