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Catalog Apps aggregates IGVF-produced and partner tools that complement the catalog itself.

App Cards

  • Each tile displays the app name and a short description curated alongside the catalog content.
  • Category badges now show whether a link is a Dataset, Prediction Model, or Companion App, so you know at a glance if you are opening measured data, a model viewer, or a complementary portal.
  • Links open in separate tabs so users can keep the catalog context while referencing external portals such as FAVOR, MaveDB, the Lipids Knowledge Portal, E2G, and the IGVF Data Portal.
  • The IGVF Catalog tile links back to /, effectively providing a “scroll to top” shortcut for users who landed here from the home page.

What each app offers

  • FAVOR (Dataset): Variant annotation matrix that mirrors the coding scores shown inside IGVF tables, ideal for bulk lookups.
  • MaveDB (Dataset): Community hub for multiplexed variant effect experiments, including IGVF VAMP-seq and SGE releases, with per-variant activity scores.
  • IGVF Coding Variants (Dataset): Purpose-built view of IGVF coding variant measurements so you can search genes or variants and see the same experimental rows as in the catalog.
  • E2G (Prediction Model): Explorer for enhancer-to-gene predictions across biosamples; useful for comparing regulatory links against the catalog’s region dashboards.
  • RegulomeDB (Companion App): Quick scoring of noncoding variants using regulatory evidence; helpful when triaging leads found in IGVF browsing.
  • Lipids Knowledge Portal (Companion App): Disease-focused portal that layers IGVF lipids data with cohort summaries tailored to cardiometabolic questions.
  • IGVF Data Portal (Dataset): Entry point to the raw files and harmonised metadata that underpin the catalog summaries.
  • DACC IGVF Catalog (Companion App): The catalog itself, available as a tile so you can hop back to the home view after exploring partner tools.
Centralising these partner links means scientists can pivot between IGVF knowledge graph summaries and specialised external resources without maintaining a separate bookmark list.