Genome-variant analysis is commonly organized as linear pipelines for annotation, filtering, and prioritization. Digital Genome Workstation (DGW) complements these workflows with a local desktop environment for interactively constructing, editing, and comparing alternative diploid variant configurations derived from a selected VCF sample. Inspired by digital audio workstations, DGW represents genome configurations as tracks and exposes modular devices for editing, evidence retrieval, analysis, and visualization. Edits are reversible and provenance-preserving, allowing alternative configurations to be generated and compared without modifying the source VCF. DGW includes devices for reproducible variant perturbation (Mutation Generator), consequence-guided allele exploration (Genome Optimizer), and interpolation between existing tracks (Genome Morph). We evaluated these operations using the public 1000 Genomes HG00103 exome. Across ten seeded perturbations of 52 TTN SNV positions, Genome Optimizer reduced an additive predicted-consequence score from 40.43–42.11 to 34.69 by modifying 11–14 positions per run, whereas an analogous BRCA2 analysis produced no improving edits. Optimized TTN tracks converged on the same score while retaining distinct allele configurations, and Genome Morph reproducibly generated intermediate configurations between selected tracks. These experiments demonstrate reproducible manipulation and comparison of alternative variant states rather than biological optimization or restoration of gene function. DGW is freely available for Linux, macOS, and Windows under the Apache License 2.0 at https://github.com/mrueda/digital-genome-workstation, with human resource packs for GRCh37 and GRCh38.
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Manuel Rueda (2026) studied this question.
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