Tommi Mäklin

Postdoctoral researcher | University of Helsinki

View all of my publications on Google Scholar.



Themisto: a scalable colored k-mer index for sensitive pseudoalignment against hundreds of thousands of bacterial genomes

Jarno N Alanko, Jaakko Vuohtoniemi, Tommi Mäklin, and Simon Puglisi

preprint, bioRxiv, 2023

Themisto is a method for both building and querying colored de Bruijn graphs that was originally introduced in my mGEMS paper in 2021. The 2023 version of Themisto implements an order of magnitude faster build and query algorithms than the state-of-the-art at the time, and introduces a new hybrid method of pseudoalignment that combines ideas from existing algorithms.


Strong pathogen competition in neonatal gut colonisation

Tommi Mäklin, Harry A Thorpe, Anna K Pöntinen, Rebecca A Gladstone, Yan Shao, Maiju Pesonen, Alan McNally, Pål J Johnsen, Ørjan Samuelsen, Trevor D Lawley, Antti Honkela, and Jukka Corander

Nature Communications, 2022

We applied the mSWEEP and mGEMS methods to study colonization dynamics of Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis at the lineage-level. Our results highlighted a strong competitive advantage for the first strain to colonize the gut of a newborn but found no selection for hospital-adapted or disease-associated lineages. For more information, please see the press release by the Wellcome Sanger Institute.


Bacterial genomic epidemiology with mixed samples

Tommi Mäklin, Teemu Kallonen, Jarno N Alanko, Ørjan Samuelsen, Kristin Hegstad, Veli Mäkinen, Jukka Corander, Eva Heinz, and Antti Honkela

Microbial Genomics, 2021

This article introduces the mGEMS pipeline for deconvoluting short-read sequencing data from samples containing multiple lineages of the same bacterial species. mGEMS assigns each read to one or more reference lineage(s) and produces an assignment of the reads that can replace isolate sequencing data in standard epidemiological analyses applied to metagenomic data. mGEMS has been used in study of within-host diversity of Streptococcus pneumoniae and Enterobacteriaceae colonization dynamics.

High-resolution sweep metagenomics using fast probabilistic inference

Tommi Mäklin, Teemu Kallonen, Sophia David, Christine J Boinett, Ben Pascoe, Guillaume Méric, David M Aanensen, Edward J Feil, Stephen Baker, Julian Parkhill, Samuel K Sheppard, Jukka Corander, and Antti Honkela

Wellcome Open Research, 2021

This article describes the mSWEEP method for estimating the relative abundances of lineages of a bacterial species in a set of short-read sequencing data. mSWEEP is closely tied with the mGEMS tool and the two are typically used together.