Development of a bioinformatics workflow to be used in detecting antiviral resistance using the next generation sequencing method

Arslan, N (2024) Development of the Bioinformatics Workflow to be Used in the Detection of Antiviral Resistance with the Next Generation Sequencing Method. Istanbul University- Cerrahpaşa Graduate Education Institute, Department of Medical Microbiology. Master's Thesis. Istanbul. With combined antiretroviral drug therapy (ART), which started to be used in the treatment of Human Immunodeficiency Virus (HIV) in 1996, the life span and quality of life in HIV- positive people has increased significantly. On the other hand, the rapidly developing drug resistance in HIV poses an obstacle to effective treatment. The data of the virus genome obtained by Next Generation Sequencing (NGS), which is used to detect HIV drug resistance, is used to detect resistances caused by mutations using various commercial databases and evaluation programs. Kit manufacturers and some software companies offer solutions that basically charge per evaluation. This increases the already relatively expensive next- generation sequencing testing costs. In this study, it was aimed to create and test the performance of a bioinformatics workflow that enables free and fast analysis of NGS data used in HIV antiretroviral resistance analysis and can generate common sequence output. In the Microbiology Laboratory of Istanbul University Cerrahpaşa Faculty of Medicine, Department of Medical Microbiology, drug resistances against protease, reverse transcriptase and integrase inhibitors were routinely studied using NGS from HIV-positive patient samples between 2019 and 2021. The data of 60 HIV-positive patients with different resistance profiles, 30 with ART resistance and 30 without ART resistance, who had previously applied to our institution for routine testing, whose studies were completed and whose results we archived, were included in our study. The data obtained as a result of sequencing during routine work were analyzed using the paid DeepCheck (ABL, USA) analysis program. In the workflow we developed, different alignment algorithms were first tested, variant identification from the created alignments, creation of a common sequence that could contain 5% variants for each case, and the workflow performances were tested by comparing these data. In addition, by comparing the results we obtained with the analysis results obtained through DeepCheck, which is used in routine studies, a new analysis algorithm was developed and the accuracy and usability of the developed program were examined. When the analyzes made with BWA and Bt2 algorithms were compared as a result of the resistance analysis performed with the developed flow, all algorithms were found to be compatible in terms of single nucleotide changes for the analyzed region in 25 of 30 cases in which resistance was detected. However, in 5 cases, the BWA algorithm and the standard report result were incompatible. We found the workflow created by using the BWA and bowtie-2 algorithms tested in this thesis study together with Samtools and Ivar to be useful, fast and cost-effective in HIV next-generation sequence analysis evaluations. In these evaluations, it may be recommended that the quality of the device output data be reviewed before analysis, and that data at the Q30 (99.9% accuracy) level be included in the analysis to detect minor variants, and depth analyzes be performed at the 1000x level.