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Talos

Talos is a scalable, open-source variant prioritisation tool designed to support automated reanalysis of genomic data in rare disease. It identifies candidate causative variants in known disease genes by integrating static annotations (e.g. population frequency, predicted consequence) with dynamic knowledge sources such as ClinVar and PanelApp Australia. Talos applies a set of configurable, rule-based logic modules aligned with ACMG/AMP criteria and prioritises variants consistent with expected mode of inheritance and, optionally, patient phenotype.

While Talos can be used for one-off reanalysis of individual families or cohorts, its core design is optimised for routine, cohort-scale reanalysis. By comparing current annotations with prior results, Talos highlights variants that have become reportable due to newly available evidence — such as new gene–disease or variant–disease relationships — since the last analysis cycle.

A full description of the method and its validation in large clinical and research cohorts is available in our preprint: medRxiv 2025.05.19.25327921.

Note - whether you are a new Talos user, or have an implementation already, we encourage you to run the preparation workflow with each update!

Latest Changes

[12.3.1] - 2026-11

Fixed

  • Single-sample VCF inputs (ss_vcf_dir) are now split and left-aligned per sample before merging, instead of after (#729). When an allele was part of a multi-allelic record in one sample but a separate record in another, the merge split it across two rows, each with only some samples' genotypes. That produced false de novo calls and dropped alleles. Cohorts annotated from ss_vcf_dir before this fix keep the bad rows until their ${cohort}_annotated/ directory is deleted and they are re-annotated. A variant written twice within one sample's VCF is now also deduplicated

[12.3.0] - 2026-10

Added

  • New SV category, aimed at matching CNVs to PanelApp's regulatory regions
  • These are interpreted separately from other Genes, SVs, and STRs
  • A match is made when a CNV overlaps a region by a minimum of x%, and is DUP/DEL matched

[12.2.1] - 2026-10

Changed

  • SVs with non-symbolic ALT alleles are skipped prior to running GATK SvAnnotate

[12.2.0] - 2026-09

Added

  • Panel confidence (Red/Amber/Green) is now recorded in the history, and if a variant is newly promoted to Green, this is identified in the report
  • The Report has Emojis next to the date if variant evidence changes:
    • ➕ - Seen previously, but has additional categories in this round (this was briefly 🆕)
    • 💫 - ClinVar star count has increased
    • 🎯 - Newly phenotype-matched
    • 🚦 - Newly Green in PanelApp
  • STRs are now accessible via the Nextflow implementation. This requires a STRipy JSON -> VCF conversion using src/talos/scripts/stripy_json_to_vcf.py
  • By default, STRs are only analysed on panels phenotypically-matched to the participant to suppress incidental findings.

[12.1.0] - 2026-09

Added

  • A new SV-specific category has been added - PREDICTED_EXONIC_BND annotations from SvAnnotate are now considered as an impactful category.
  • BNDs were a blind spot for Talos, as the PREDICTED_LOF SV annotation was never applied to BNDs

Changed

  • Debian Bullseye has reached EOL, so the default image builds have moved up to Trixie/Java 21
  • Java 21 is not officially validated by Hail, but has worked in local testing. As far as we are aware the only risk of incompatibility with Hail/Java is relevant to Google Dataproc, which will not apply to most users.

Full changelog

Where to next

  • Getting Started Install the requirements, download annotation resources, and run your first cohort.

  • Features Logic modules, reanalysis mode, phenotype matching, and what Talos is (and isn't) for.

  • Configuration Full reference for the Talos TOML config and Nextflow parameters.

  • SVs Details on the SV workflow and results.

  • Changelog Release history and version-by-version changes.

When to use Talos

Talos is best suited for scenarios where:

  • You are performing routine reanalysis of undiagnosed individuals (e.g. monthly or quarterly).
  • You want to detect variants that have become reportable due to updates in gene–disease or variant–disease knowledge.
  • You aim to minimise the number of variants requiring manual review, optimising for specificity over sensitivity.
  • You are working with exome or genome sequencing data from previously analysed research or clinical cohorts.
  • You need a scalable, reproducible pipeline for family-based or cohort-scale analysis.

Talos is not currently designed for:

  • Identifying novel candidate disease genes or gene discovery.
  • Analysing short tandem repeats (STRs), mosaic variants, or variants outside standard clinical reporting regions.

Support for some of these variant types may be added in future releases.

Citation

If you use Talos in your research or clinical workflow, please cite:

Welland MJ, Ahlquist KD, De Fazio P, et al. Scalable automated reanalysis of genomic data in research and clinical rare disease cohorts. medRxiv 2025.05.19.25327921; https://doi.org/10.1101/2025.05.19.25327921

@article{welland2025talos,
  title     = {Scalable automated reanalysis of genomic data in research and clinical rare disease cohorts},
  author    = {Welland, Matthew J and Ahlquist, KD and De Fazio, Paul and Austin-Tse, Christina and Pais, Lynn and Wedd, Laura and Bryen, Samantha and Rius, Rocio and Franklin, Michael and Hall, Giles and et al.},
  journal   = {medRxiv},
  year      = {2025},
  doi       = {10.1101/2025.05.19.25327921},
  url       = {https://www.medrxiv.org/content/10.1101/2025.05.19.25327921},
}