Vincent‐Philippe Lavallée

This study examines the dynamic changes in the immune microenvironment of paediatric solid tumours over time, revealing a shift toward immunosuppressive and tolerogenic states.

EPCY ranks genes by predictive power using cross-validated classifiers and density estimation, outperforming DEG-based methods in selecting robust candidate genes.

Decipher is a deep generative model that integrates single-cell RNA-seq data to visualize and characterize transitions between normal and perturbed cell states across different diseases.

This study identifies DEK::NUP214 as an XPO1-dependent transcriptional activator of leukemia genes, showing selective response to XPO1 inhibitors in t(6;9) AML cases.

The paper replicates a GWAS signal near HLA-DQA2 associated with AML risk using a disease-only cohort and external population-based controls, finding a stronger effect in patients with NPM1 mutations.

This study demonstrates real-time transcriptomic profiling using nanopore sequencing and a neural network classifier to classify childhood acute lymphoblastic leukemia subtypes efficiently.

This paper introduces km, a method for detecting targeted mutations in AML using unaligned RNA-Seq reads, showing it is fast, accurate, and limited by sequencing depth.