Exploring phage-host interactions in the human microbiome: Development of a dataset for benchmarking predictive models

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master_Satova_Elina_2025.pdf (3.49 MB)

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School of Science | Master's thesis
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Date

2025-05-26

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Bioinformatics and Digital Health

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Degree programme

Master's Programme in Life Science Technologies

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en

Pages

74

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Abstract

The prediction of bacteriophage hosts and phage-host dynamics in the human microbiome is critical for understanding their role in modulating human health and in the development of potential therapeutic treatments. While several bioinformatic tools are available for predicting phage-host interactions, their evaluation is complicated by the lack of high-quality, representative datasets. In this study, a comprehensive benchmark dataset was developed to assess the performance of phage host prediction tools. The initial metagenomic assembly, obtained from the Pasolli et al. (2019) study, included 154,723 microbial genomes and was preprocessed. Viral sequences from the metagenomic dataset were identified using the VirSorter2 tool and the quality and completeness of the viral dataset were assessed using the CheckV tool. This study produced a dataset for evaluating phage host prediction tools, along with an additional metadata table and visual analysis of the initial metagenomic assembly and viral dataset. Recommendations for tool optimization were also provided. Future work can use this dataset to benchmark widely used phage-host prediction tools.

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Supervisor

Lähdesmäki, Harri

Thesis advisor

Vatanen, Tommi

Keywords

human microbiome, bacteriophages, phage hosts prediction, benchmark dataset, bioinformatics, viral prediction tools

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https://urn.fi/URN:NBN:fi:aalto-202506164720

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[dipl] Perustieteiden korkeakoulu / SCI