Jonas Demeulemeester

This study uses single-cell and spatial multi-omics to analyze a malignant peripheral nerve sheath tumor, revealing chromosomal instability drives phenotypic diversity and spatial-temporal evolution.

The paper identifies cis-acting genetic variants affecting enhancer function in Parkinson's Disease using multi-omics data and develops models to predict their regulatory impact.

LRSomatic is a pipeline for somatic variant calling in long-read sequencing data, achieving state-of-the-art performance on cancer samples and resolving complex variants.

SPLONGGET enables comprehensive genotype-phenotype analysis by integrating long-read single-cell genome, transcriptome, and open chromatin profiling in thousands of cells.

The paper benchmarks structural variant callers in cancer genomics and recommends a consensus approach combining Delly, GRIDSS, Manta, and SvABA for improved performance.

This study identifies acidic patches in the MYC N-terminal disordered domain essential for oncogenesis and chromatin interaction, offering new therapeutic targets.

This paper introduces Gtag&T-seq, a low-cost single-cell multi-omics method that reveals cell state plasticity and treatment response in melanoma subclones.

The paper compares single-cell whole genome amplification methods and reference genomes for detecting somatic copy number variants in human brain tissue.

The paper identifies a novel mechanism where focal deletions of an intronic element in FTO lead to IRX3 activation in T-ALL through enhancer hijacking.

This study uses single-cell genome-and-transcriptome sequencing to analyze the impact of chromosome instability on cellular states and development in human preimplantation embryos.

The paper maps enhancer gene regulatory networks (GRNs) in liver cell types and identifies TFs governing hepatocyte zonation states using multiomics and deep learning.

The paper reports a genome-wide map of neuropeptide-GPCR interactions in C. elegans, identifying 461 cognate peptide-GPCR pairs and uncovering their evolutionary conservation.

The paper benchmarks 31 subclonal reconstruction algorithms on simulated tumours, finding that algorithm choice significantly impacts performance and no single algorithm excels across all tasks.

The paper identifies and characterizes enhancer activity in melanoma cell states using MPRA and DeepMEL2, showing AP-1 drives MES enhancers and SOX/MITF influence MEL enhancers.

The paper analyzes somatic substitutions in non-unique regions of the human genome across 2,658 cancers, revealing hidden mutations in coding sequences and regulatory elements.

The paper uses a deep learning model on melanoma genomes to prioritize enhancer mutations by analyzing allelic imbalance in chromatin accessibility and gene expression.

This paper introduces CAMDAC, a method to deconvolve tumor-normal DNA methylation profiles while accounting for copy number changes, revealing epigenetic instability and distinct patterns in lung cancer.

The paper quantifies tumor-specific total mRNA expression from bulk data and shows its association with clinical outcomes across 15 cancer types.

This study identifies genomic and methylation patterns associated with benign metastases and malignant transformation in giant cell tumour of bone.

The paper analyzes somatic retrotransposition events in 2,954 cancer genomes, identifying L1 insertions as significant contributors to structural variations and oncogenesis.

The paper describes the PCAWG project's large-scale analysis of cancer whole genomes across multiple computing environments, producing validated consensus variants for downstream research.