A modular and scalable web platform for computational phylogenetics
CoRR(2024)
Abstract
Phylogenetic analysis, which allow to understand the evolution of bacterial
and viral epidemics, requires large quantities of data to be analysed and
processed for knowledge extraction. One of the major challenges consists on the
integration of the results from typing and phylogenetic inference methods with
epidemiological data, namely in what concerns their integrated and simultaneous
analysis and visualization. Numerous approaches to support phylogenetic
analysis have been proposed, varying from standalone tools to integrative web
applications that include tools and/or algorithms for executing the common
analysis tasks for this kind of data. However, most of them lack the capacity
to integrate epidemiological data. Others provide the ability for visualizing
and analyzing such data, allowing the integration of epidemiological data but
they do not scale for large data analysis and visualization. Namely, most of
them run inference and/or visualization optimization tasks on the client side,
which becomes often unfeasible for large amounts of data, usually implying
transferring data from existing databases in order to be analysed. Moreover,
the results and optimizations are not stored for reuse. We propose the PHYLOViZ
Web Platform, a cloud based tool for phylogenetic analysis, that not only
unifies the features of both existing versions of PHYLOViZ, but also supports
structured and customized workflows for executing data processing and analyses
tasks, and promotes the reproducibility of previous phylogenetic analyses. This
platform supports large scale analyses by relying on a workflow system that
enables the distribution of parallel computations on cloud and HPC
environments. Moreover, it has a modular architecture, allowing easy
integration of new methods and tools, as well as customized workflows, making
it flexible and extensible.
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