Jeroen Gilis

IsoformSwitchAnalyzeR v2 identifies and analyzes functional isoform switches in long-read and single-cell sequencing data, showing disease-relevant changes in Alzheimer's and glioblastoma.

The paper introduces a method to enhance RNA-seq tools for differential usage, aberrant splicing, and expression retrieval by modifying normalization offsets and presents a faster tool for outlier detection.

The paper develops a workflow for differential detection analysis in single-cell RNA-seq data and shows it provides complementary information to differential expression analysis.

This paper evaluates strategies to address pseudoreplication in multi-patient scRNA-seq data, finding that Poisson GEEs and pseudobulk approaches outperform single-cell methods.

Combining pseudobulk differential expression, cell-type specificity, sample prevalence and NicheNet-v2 ligand activity, MultiNicheNet ranks condition-specific ligand-receptor-target signaling in multi-sample scRNA-seq with batches or multifactor designs.

This paper meta-analyzes single-cell method benchmarks to identify challenges in extensibility, interoperability, and reproducibility.

satuRn analyzes differential transcript usage in bulk and single-cell RNA-seq data, offering scalability and accurate false discovery rate control.

The paper identifies issues in re-analyzing observational omics studies, highlighting problems with false positives, method limitations, and lack of confounders in public metadata.