A deep learning-based phylogenetic tool powered by TIPs-VF

Identification: Focuses on recognizing the origin or species of a genetic sequence. Covary can accurately identify unknown samples by matching them to the closest evolutionary signatures in its reference set, provided uniform sequences are used. For example, identification can be applied in pathogen surveillance to pinpoint the source of an emerging viral outbreak.

Relationship: Seeks to determine evolutionary connections between sequences. Covary reconstructs phylogenetic trees that reveal lineage divergence, ancestry, and clonal evolution, providing a map of how organisms or mutations are connected. For example, this can be used to trace tumor clonal evolution and understand how different subclone genotypes may emerge during cancer progression.

Prediction: Estimates potential evolutionary outcomes or mutational trajectories. Covary can forecast likely future variants or clonal progressions, supporting applications in epidemiology and cancer research. For example, predictive workflows can model how viral genomes might evolve anti-viral resistance or how tumor mutations may drive treatment relapse.