Computational detection of human papilloma virus in the cervical cancer genome

Abstract: Global research and development have witnessed new horizons in technological advancements, especially in the use of new-generation bioinformatic tools to solve human needs. Cervical cancer, caused by a sexually transmitted virus like human papillomavirus (HPV), is one of the most common cancers threatening women's health. The main aim of the study is to evaluate existing Next-generation pipelines for detection of HPV in cervical cancer. The method includes data retrieval, which involves careful selection and downloading of 30 metagenomic data (in FASTA-Q format) from the Human Microbiome Project database. The implementation phase of the study involved setting up and configuring the virus detection tools (HPViewer, VirusSeq and VirusFinder 2.0). All the tools were run on default settings to analyze the metagenome samples using the instructions provided by their authors. The result showed that the tools detected HPV. The HPViewer demonstrated a higher level of HPV detection, followed by VirusSeq and then VirusFinder 2. The HPViewer had the shortest run time, completing an analysis in 24.1 seconds, followed by VirusFinder 2 in 208 seconds and VirusSeq took 4200 seconds (1 hour, 10 minutes to run). HPViewer demonstrated an outstanding sensitivity of 100%, VirusFinder 2 (45.5 %) and VirusSeq (63.6%). In conclusion, the present study underscored the trade-offs between speed, accuracy, and resource consumption between bioinformatics tools for HPV detection. Each of the tools exhibited unique strengths and limitations; however, they provided valuable options for HPV detection.