Guillaume Méric

The paper analyzes bacterial diversity and strain dynamics in the infant respiratory microbiome using whole genome sequencing and metagenomics, revealing age-dependent shifts in dominant taxa and expanding reference genomes for airway microbes.

This study evaluates deep learning methods for polygenic prediction, showing that MLP benefits most from larger sample sizes and one-hot encoding improves performance across methods.

This study integrates polygenic risk scores and gut metagenomic data to improve prediction of common diseases, showing enhanced predictive performance over conventional risk factors.

This study identifies major technical variations in microbiome data and evaluates a batch correction tool to minimize their impact on downstream analyses.

This study uses gut microbiome data and machine learning to improve liver disease risk prediction, showing that combining microbiome features with conventional risk factors enhances model performance.

This study quantifies the carbon footprint of bioinformatics analyses and identifies strategies to reduce energy consumption and CO2 emissions.

In 5,959 Finns with genotypes and stool metagenomes, GWAS found 583 independent SNP-taxon associations; dairy intake modified LCT effects on Bifidobacterium, and ABO-linked Faecalicatena lactaris tracked secretor status.

Trycycler improves bacterial genome assemblies by combining multiple long-read assemblies, reducing errors and improving accuracy when followed by polishing with Medaka and Pilon.

This paper introduces OGUs, a metagenome analysis method that uses sequence alignment hits to reference genomes for community analysis, showing better performance in predicting biological traits than taxonomic or 16S rRNA methods.

This study identifies 118 genetic loci associated with 2,319 metabolite features and finds 46 causal effects of metabolites on common diseases using genome-wide association and Mendelian randomization.

The paper shows improved metagenomic reference databases increase read classification rates and affect downstream microbiome analysis.

The paper introduces mSWEEP, a method for high-resolution bacterial lineage quantification from plate sweeps, showing improved accuracy in detecting and estimating abundances of bacterial lineages.