Matthieu Foll

This study identifies three distinct spliceosomic profiles in pancreatic neuroendocrine tumors linked to clinical and molecular characteristics and potential therapeutic targets.

PACMOS projects query cancer samples into pretrained MOFA latent factor spaces for classification.

The paper presents a large multi-omic dataset of lung neuroendocrine tumours, including genomics, transcriptomics, methylation, spatial proteomics, and histopathology, enabling comprehensive molecular and morphological analysis.

This paper presents a comprehensive molecular characterization of Malignant Pleural Mesothelioma using multi-omics data from 120 patients, integrating with existing datasets to create an interactive molecular phenotype map.

This study identifies eight novel lung cancer susceptibility loci and shows that germline variants related to smoking and DNA repair influence somatic mutation burden in lung tumors.

The paper extends the F-model to linked loci using a hidden Markov model to detect selection, showing increased statistical power and identifying selection in the human genome.

Needlestack is a variant caller that improves sensitivity for low abundance mutations by learning sequencing error rates from multi-sample data.

The paper reconstructs 9000 years of agricultural diet in Asia and shows its impact on genetic variation in 29 Asian populations, identifying genes related to metabolism as targets of dietary-driven selection.

The paper investigates how genetic variation in wild mice affects fitness by linking genotype to phenotype and allele frequency changes through field and lab experiments.

The paper identifies convergent genetic adaptations to high altitude in Asian and American populations using a hierarchical Bayesian method applied to a large SNP dataset.