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In this repository we provide an implementation of the VERSO (Viral Evolution ReconStructiOn) framework.
VERSO is an algorithmic framework that processes variants profiles from viral samples, to produce phylogenetic models of viral evolution from clonal variants and to subsequently quantify the intra-host genomic diversity of samples. VERSO includes two separate and subsequent steps, which are perfomed via the scripts provided in this repository.
The manuscript of the method is available at this link: https://www.cell.com/patterns/fulltext/S2666-3899(21)00022-2
VERSO STEP #1 employs a probabilistic maximum-likelihood framework for the reconstruction of robust phylogenetic trees from binarized mutational profiles of clonal variants.
VERSO STEP #1 takes as input: a n (samples) × m (variants) binary mutational profile matrix, as defined on clonal SNVs only. In this case, an entry in a given sample is equal to 1 (present) if the VF is larger than a certain threshold (in our analyses, equal to 90%), it is equal to 0 if lower than a distinct threshold (in our analyses, equal to 5%), and is considered as missing (NA) in the other cases.
VERSO outputs: (i) a phylogenetic model where each leaf correspond to a sample, whereas internal nodes correspond to accumulating clonal variants (in Newick format), (ii) the corrected clonal genotype of each sample.
VERSO is provided as an R open source tool.
To run the VERSO STEP #1 tool please go to the folder: https://github.com/BIMIB-DISCo/VERSO/tree/VERSO/VERSO_STEP_1 and refer to the related readme, which includes instructions and guidelines.
In the second step, VERSO takes into account the variant frequency profiles of groups of samples with the same clonal genotype (identified via VERSO STEP #1), in order to characterize their intra-host genomic diversity and visualize it on a low-dimensional space.
VERSO STEP #2 takes as input a n (samples) × m (variants) variant frequency (VF) profile matrix, in which each entry includes the VF ∈ (0,1) of a given mutation in a certain sample, after filtering out: (i) the clonal variants employed in STEP #1 and (ii) the minor variants possibly involved in homoplasies.
As output, VERSO STEP #2 delivers both the partitioning of samples in homogeneous clusters and the visualizationin a low-dimensional space, also allowing to label samples according to other covariates, such as, e.g., collection date or geographical location.
VERSO STEP #2 is provided as a Python script which employs the SCANPY suite of tools.
To run the VERSO STEP #2 tool please go to the folder: https://github.com/BIMIB-DISCo/VERSO/tree/VERSO/VERSO_STEP_2 and refer to the related readme, which includes instructions and guidelines.
Please feel free to contact us if you have problems running our tool at daniele.ramazzotti1@gmail.com or d.maspero@campus.unimib.it.