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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

[12.0.2] - 2026-09

Added

  • Dockerfile can now take build arguments for base image and Java version. The default version is now approaching EOL, but due to Hail's dependency pinning, Bullseye is the latest Debian version with Java 11 available as standard
  • Documented that Java >11 is not explicitly validated by Hail, but building on a more modern Java & base does seem to work in local testing

[12.0.1] - 2026-08

Added

  • New NF workflow output - each run creates a new file, suitable for use as input in the next round of analysis
  • the new file contains the same verbatim content as the input file, except for the history column, updated to contain the cohort's output file from the current run

[12.0.0] - 2026-08

Breaking

Input TSV parsing has been changed, and is now more fully described in the README. Instead of requiring specifically named asset files to represent absent inputs (e.g. assets/NO_HISTORY instead of not providing results from a prior analysis), the parsing now intelligently detects that either a completely missing column, or an empty value in that column, represent an absent input. Any input files which contain these asset files will break on versions >= 12, as the 0-Byte sentinel file will be parsed as a real input.

Apologies for this breaking change, but the original solution was bad, and was a product of not finding a better solution in NextFlow. Flexible TSV parsing and empty-channel defaults should make this much simpler to manage.

Fixed

A couple of workflow elements are now fixed:

  • file discovery in cloud environments was broken, i.e. the glob for previously generated MT files, or the glob for input VCFs and corresponding indices. Due to string handling these were stripping the s3:// or gs:// prefix, leading to a pseudo-local path being checked, which would fail to find existing files.
  • channel mixing is now fixed - if SV columns were provided but empty, the Small variant and SV channel mixing would return an empty join, so ValidateMoi and downstream stages would never run.

Added

SV inputs and how to provide them are discussed more in the documentation pages.

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},
}