The Single-cell Analysis team of SaeysLab develops open-source algorithms that leverage single-cell transcriptomics data to further our biological understanding of how cells cooperate across space and time to perform various functions.

How can prior biological knowledge and various omics technologies be combined to infer cell-cell communication processes, both within and across samples of healthy and diseased tissue?

To further advance the field of single-cell transcriptomics, this team also performs benchmarks of various algorithms and pipelines. What are the most suitable methods, for example to infer a trajectory or perform spatial deconvolution?