ViTAL deep learning models for lineage assignment under low coverage

ViTAL, is a lineage assignment algorithm which inputs
a low-coverage genome, transforms it into embedded genome
fragments which are then fed into a classification neural
network, that outputs the most likely lineages the input genome
might belong to. The ViTAL algorithm is therefore divided into
preprocessing phase (MinHash) followed by embedding, and the
classification phase (Vision Transformer).

The upload contains trained models for lineage assignment.