Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS - PaRis AI Research InstitutE
Article Dans Une Revue Bioinformatics Année : 2024

Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS

Résumé

Motivation: The molecular identity of a cell results from a complex interplay between heterogeneous molecular layers. Recent advances in single-cell sequencing technologies have opened the possibility to measure such molecular layers of regulation. Results: Here, we present HuMMuS, a new method for inferring regulatory mechanisms from single-cell multi-omics data. Differently from the state-of-the-art, HuMMuS captures cooperation between biological macromolecules and can easily include additional layers of molecular regulation. We benchmarked HuMMuS with respect to the state-of-the-art on both paired and unpaired multi-omics datasets. Our results proved the improvements provided by HuMMuS in terms of transcription factor (TF) targets, TF binding motifs and regulatory regions prediction. Finally, once applied to snmC-seq, scATAC-seq and scRNA-seq data from mouse brain cortex, HuMMuS enabled to accurately cluster scRNA profiles and to identify potential driver TFs.
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Dates et versions

hal-04728076 , version 1 (11-10-2023)
hal-04728076 , version 2 (09-10-2024)

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Remi Trimbour, Ina Maria Deutschmann, Laura Cantini. Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS. Bioinformatics, 2024, 40 (5), pp.btae143. ⟨10.1093/bioinformatics/btae143⟩. ⟨hal-04728076v2⟩
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