moonicu

NeoVUS is a point-of-care tool for NICU clinicians who hit a variant of uncertain significance (VUS) in a neonatal genomic report. Existing tools either rank variants across a whole exome (Exomiser) or serve genetics professionals (VarSome) — none give a neonatologist an actionable, auditable interpretation of ONE already-flagged variant. What I built: enter a variant as written on the report (c./p. HGVS, rsID, or coordinate) plus the baby's phenotypes, and NeoVUS returns candidate diseases re-ranked by phenotype match, a neonatal checklist of symptoms with cited work-up and follow-up actions, the variant mapped onto its protein domain (UniProt/AlphaFold), and a plain-language summary — where every claim links back to its source database. The report tracks its own citations and flags any unsupported claim, so the clinician verifies rather than trusts a black box. What I found: on ClinVar variants reclassified across the VUS boundary, NeoVUS's transparent in-silico evidence agreed with the eventual reclassification 84.8% of the time, at 100% pathogenic precision — validated on open data, with no ClinVar label used as a feature. Why it matters: rapid genome sequencing is reaching the NICU faster than neonatologists have tools to interpret it at the bedside, and NeoVUS puts a transparent, evidence-traceable first read in their hands. The tool is actively being upgraded: a calibrated, ACMG-aware v2 is already in development (live at https://neovus2.streamlit.app, code at https://github.com/moonicu/neovus2) — it adds a provisional point-based ACMG classification, calibrated PP3/BP4 thresholds, PVS1/PS1/PM5/PM1 evidence drawn from gnomAD gene constraint and same-residue ClinVar, and clinician-supplied family/functional evidence (e.g. a confirmed de novo) that re-classifies the variant live at the bedside. Open-source (MIT), reproducible, open public data only.