Software rapidly tracks viral variants with high accuracy to aid outbreak responses

by Jessica Colarossi, Broad Institute of MIT and Harvard

edited by Lisa Lock, reviewed by Robert Egan

Lisa Lock

Scientific Editor

Meet our editorial team
Behind our editorial process

Robert Egan

Senior Editor

Meet our editorial team
Behind our editorial process Editors' notes

This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

peer-reviewed publication

trusted source

proofread

The GIST Add as preferred source

It was mid-2020, and Patrick Varilly, a software engineer and data scientist, was stuck at home, eager to help the world navigate the ongoing COVID-19 pandemic. He reconnected with Pardis Sabeti, a core institute member of the Broad Institute who was at the forefront of analyzing how the SARS-CoV-2 virus was spreading, and with Ben Fry, her longstanding collaborator and principal at Fathom Information Design, a software firm known for tackling complex data problems. Varilly had worked closely with Sabeti and Fry at MIT more than 20 years earlier.

At the time, Sabeti, Fry and their teams were studying thousands of SARS-CoV-2 genomes from COVID-19 patients to reconstruct the path of viral transmission and identify which viral variants were emerging. Normally, retracing that path—by mapping how different variants are genetically related to each other in what's called a phylogenetic tree—takes a lot of time and computing power.

Varilly, Sabeti and Fry saw an opportunity to accelerate the process while making data more accessible and easier to interpret. The result is Delphy, a new platform for rapid, interactive phylogenetic analysis. In a paper published in Nature, the researchers report how they rebuilt state-of-the-art phylogenetic tree models to make them faster, more efficient and scalable while maintaining the models' accuracy. Because Delphy runs entirely within a web browser, anyone with a laptop can perform these analyses without specialized training, software or computing infrastructure.

The researchers demonstrated that Delphy could analyze 100,000 viral DNA sequences and create phylogenetic trees 100–1,000 times faster than existing methods, reducing a task that took months to one that takes hours. To use the platform, users input sequence data, click "run," and then explore the resulting tree by moving across lineages, mutations and time to see patterns of viral evolution. This makes complex outbreak analysis more accessible to public health teams working in real time.

Delphy.bio is now freely available to anyone who needs to map virus sequence data to understand the course of an outbreak.

"Doing large-scale sequencing of viruses is now the norm, but the old tools don't work as well with such large numbers of sequences to analyze," said Varilly, first author of the new paper and a computational research scientist in the Sabeti lab. "Public health officials have a lot to juggle, so the goal of Delphy is to simplify and speed up the process as much as possible while maintaining accuracy. This project was driven by the idea that genomic sequencing can be used earlier and help contain outbreaks faster."

"The challenge was not just displaying an enormous amount of data, but making it useful," said Fry, principal at Fathom Information Design. "Delphy gives people a way to move through the tree, ask questions of it, and learn about the tree by interacting with it."

"To respond to outbreaks quickly, we need to empower frontline scientists and public health teams everywhere to carry out the most advanced analyses themselves," said Sabeti, senior author of the study. "We are tremendously excited that Delphy can bring this capability directly to the front lines, allowing people anywhere to generate rigorous insights quickly and use them to guide faster, more effective outbreak response."

Viral family tree

Viruses are constantly evolving and mutating, and often, the more a virus circulates, the more likely it is to acquire new mutations that can affect its ability to spread and infect people. Analyzing viral genomes to build phylogenetic trees allows scientists and public health officials to reconstruct outbreak timelines, visualize how and when one strain mutated from the next, and estimate how quickly the virus is changing and spreading.

These insights can inform public health interventions, and the faster experts can make decisions based on accurate and reliable data, the more likely they are to contain outbreaks quickly.

Creating phylogenetic trees from thousands of viral DNA sequences using previous methods can take weeks, even months. Varilly and his team simplified and streamlined Delphy's statistical calculations to speed up the analysis.

To test Delphy's accuracy, the team reproduced analyses from recent outbreaks and epidemics, including Ebola, Zika, SARS-CoV-2, mpox and H5N1. They report that analysis was two to three orders of magnitude faster, showing that Delphy could create a phylogenetic tree from a dataset of 100,000 virus DNA sequences within a day. Delphy can also identify key viral lineages and mutations and the timing of their emergence with the same accuracy as other commonly used methods.

Importantly, Delphy runs all calculations locally on the user's computer, so sequence data never leaves the computer. Once Delphy.bio loads, a user can do their analysis without an internet connection.

Varilly says he hopes that the public health community will adopt Delphy to help with outbreak response. "It's exciting to be at the forefront of developing new solutions that hopefully are not far away from being utilized everywhere," he said.

Publication details

Pardis Sabeti, Scalable near-real-time Bayesian phylogenetics for outbreaks with Delphy, Nature (2026). DOI: 10.1038/s41586-026-11012-6. www.nature.com/articles/s41586-026-11012-6

Journal information: Nature

Key medical concepts

Mutation

Clinical categories

Infectious diseasesLaboratory medicine Provided by Broad Institute of MIT and Harvard Who's behind this story?

Lisa Lock

BA art history, MA material culture. Former museum editor, paramedic, and transplant coordinator. Editing for Science X since 2021. Full profile →

Robert Egan

Bachelor's in mathematical biology, Master's in creative writing. Well-traveled with unique perspectives on science and language. Full profile →

Citation: Software rapidly tracks viral variants with high accuracy to aid outbreak responses (2026, September 16) retrieved 16 September 2026 from https://medicalxpress.com/news/2026-09-software-rapidly-tracks-viral-variants.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.