Background Plant viruses cause half of the emerging plant diseases and pose a great threat to agricultural crops worldwide. INEXTVIR Marie-Curie Training Network proposes the use of High-Throughput Sequencing (HTS) technologies for studying at an unprecedented depth the virome of selected agricultural crops and ecosystems across Europe. Our specific aims are: a) detecting the virome present in selected agricultural crops across Europe, b) understanding the biological and ecological impacts of the virome, c) improving virus detection capabilities in plant health diagnostic and certification settings through the development and validation of HTS methods, d) assessing the agronomic and socio-economic impact of virome and translate it into practical decision tools. Description Within the INEXTVIR project three bioinformatics PhDs are responsible for the development of methods and software tools for virome data analysis. We will evaluate the performance of existing pipelines for the analysis of HTS data for plant virus, while also developing new methods. Furthermore, we will propose an approach to simplify and automate bioinformatics pipelines to be user-friendlier by integrating them within a laboratory data management system and workflow tools. Moreover, we plan to develop a machine learning approach for decision support helping to select the most efficient pipeline based on the type of HTS dataset available and the goal of the analysis. Conclusions The simplified bioinformatics pipelines for virome HTS data analysis will make their use easier by researchers with little bioinformatic background. While working on that we are also contributing to a unified project-wide management of HTS data.