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

• DOI: 10.1101/2023.06.09.543828
• Publication Date: 2023-06-10T00:50:17Z
• Authors: Remi Trimbour; Ina Maria Deutsch...; Laura Cantini
• Keywords: 0301 basic medicine; Original Paper; [SDV]Life Sciences [q-bio]; Computational Biology; Multiomics; Mice; 03 medical and health sciences; Animals; Humans; [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]; Single-Cell Analysis; Software; Transcription Factors

AbstractThe 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.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 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.