Wouter Saelens

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Related publications (4)

Live-seq enables temporal transcriptomic recording of single cells

Bart Deplancke, Pernille Yde Rainer, Riccardo Dainese, Wanze Chen, Magda Zachara, Vincent Roland Julien Gardeux, Wouter Saelens, Orane Josiane Guillaume-Gentil

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity(1). However, scRNA-seq requires lysing cells, which impedes further molecular or functional analyses on the same cells. Here, we established Liv ...

NATURE PORTFOLIO2022

Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches

Bart Deplancke, Wouter Saelens

The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITEseq, single-nuclei sequencing, spatial tran ...

CELL PRESS2022

Recent advances in trajectory inference from single-cell omics data

Bart Deplancke, Wouter Saelens

Trajectory inference methods have emerged as a novel class of single-cell bioinformatics tools to study cellular dynamics at unprecedented resolution. Initial development focused on adapting methods based on clustering or graph traversal, but recent advanc ...

ELSEVIER2021

Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells

Wouter Saelens

We present dyngen, a multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. dyngen is more flexible than current single-cell simulation engines, and allows better method development and benchmarking, thereby stimul ...

Nature Research2021

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