SCOTTI wins PLoS Computational Biology Research Prize

Work from our group has been recognised in the PLoS Computational Biology 2017 Research Prizes. SCOTTI, which infers transmission routes from genetic and epidemiological information, won the Breakthrough in Advance/Innovation category. The citation reads
Our Breakthrough Advance/Innovation winning article presents a new computational tool, called SCOTTI (Structured COalescent Transmission Tree Inference), developed by Nicola De Maio of the University of Oxford (UK), and colleagues. De Maio says, “SCOTTI represents a convenient tool to reconstruct who-infected-whom within outbreaks… [and] has been used in particular for the study of bacterial hospital outbreaks”. It combines epidemiological information about patient exposure with genetic information about the infectious agent itself.
Work is nominated and selected as described in the announcement:
The journal invited the community to nominate their favorite 2016 published Research Articles. From these nominations the PLOS Computational Biology Research Prize Committee, made up of Editorial Board members Dina Schneidman, Nicola Segata, Maricel Kann, Isidore Rigoutsos, Avner Schlessinger, Lilia Iakoucheva, Ilya Ioshikhes, Shi-Jie Chen, and Becca Asquith, selected the winners. To help support future work, the authors of each winning paper will receive award certificates and a $2,000 (USD) prize.
You can read more about SCOTTI and the accompanying paper, written by Nicola De Maio, Jessie Wu and me, here.

BASTA: Improved method for phylogeography

This week sees publication of our paper New Routes to Phylogeography: a Bayesian Structured Coalescent Approximation in PLoS Genetics.

Phylogeography is the recovery of migration history from genome sequences, and has exploded as a field in recent years. Over a thousand papers have used contemporary sequences and ancient DNA to reconstruct migratory trends, locate the origin of outbreaks and track the spread of infectious diseases. In many high profile examples phylogeography has informed our understanding of how major human pathogens spread.

In our new paper we solve a severe and apparently widely unappreciated problem: that the most popular approaches to phylogeography are heavily biased, extremely sensitive to sampling structure and substantially underestimate statistical uncertainty. The problems stem from the treatment of migration as equivalent to mutation (discrete trait analysis; DTA), and the assumption that sampling locations are phylogeographically informative.

To solve these problems we introduce and demonstrate a new method BASTA, implemented in the phylogenetic software package BEAST2, that employs a novel approximation to enable inference under the structured coalescent – the bottom-up population genetics model of migration. Previously, methods for exact inference under the structured coalescent have proven too slow for many practical purposes, hence the need for a fast and accurate approximation.

The biases we highlight with popular phylogeography methods are much more important than might appear from what is at one level a question of model choice. To underline this, we present an analysis of around 100 Ebola virus genome sequences to investigate the emergence of human outbreaks. Epidemiological studies have found that animals act as a reservoir, maintaining the virus between the sporadic human outbreaks that have unfolded over the past four decades, a scenario that our structured coalescent-based model correctly identifies.

Remarkably, DTA, the de facto standard method for phylogeography, wrongly concluded with high confidence that Ebola has been maintained since 1976 by undetected human-to-human transmission between outbreaks. Although such a conclusion would never be believed in the case of Ebola, it makes clear the potential for highly misleading inference about transmission that could, for much less well understood diseases, have serious implications for public health policy.

BASTA is the result of a lot of hard work by Nicola De Maio, who is a James Martin Fellow at the Oxford Martin School Institute for Emerging Infections, with help from Jessie Wu and Kathleen O'Reilly. You can read the paper here and download BASTA here.