Robrecht Cannoodt

anndataR enables interoperability between R and Python by allowing native reading and writing of H5AD files in R, with compatibility testing and conversion to R single-cell objects.

The paper presents a longitudinal multimodal benchmarking dataset and competition to evaluate modality prediction methods for gene regulatory inference, showing top models outperform existing approaches.

geneRNIB provides a benchmark for gene regulatory network inference, showing simpler models often outperform complex ones in perturbation-informed metrics.

A NeurIPS 2021 benchmarking competition evaluated over 2600 submissions from 280 competitors across three multimodal single-cell integration tasks using a purpose-built benchmarking dataset and cloud evaluation pipeline.

dyngen is a multi-modal simulation tool that enables the development and testing of new computational methods for single-cell omics analyses.

The paper introduces a generalized additive model framework for trajectory-based differential expression analysis in single-cell RNA-seq data, enabling flexible inference of within and between lineage gene expression differences.

The paper presents a comprehensive human transcriptome atlas with single-nucleotide resolution, identifying thousands of novel RNA species and regulatory interactions.

This paper benchmarks 29 trajectory inference methods on real and synthetic datasets, identifies top-performing tools, and provides guidelines for users.

Unsupervised trajectory inference by SCORPIUS outperformed Wanderlust, Monocle and Waterfall across ten scRNA-seq datasets and predicted falling protein synthesis during dendritic cell development, validated in vivo.