Language
English
Publication Date
3-1-2024
Journal
NAR Genomics and Bioinformatics
DOI
10.1093/nargab/lqae007
PMID
38312937
PMCID
PMC10836941
PubMedCentral® Posted Date
2-2-2024
PubMedCentral® Full Text Version
Post-print
Abstract
Recent advances in single-cell multi-omics technologies have provided unprecedented insights into regulatory processes. We introduce TREASMO, a versatile Python package designed to quantify and visualize transcriptional regulatory dynamics in single-cell multi-omics datasets. TREASMO has four modules, spanning data preparation, correlation quantification, downstream analysis and visualization, enabling comprehensive dataset exploration. By introducing a novel single-cell gene-peak correlation strength index, TREASMO facilitates accurate identification of regulatory changes at single-cell resolution. Validation on a hematopoietic stem and progenitor cell dataset showcases TREASMO's capacity in quantifying the gene-peak correlation strength at the single-cell level, identifying regulatory markers and discovering temporal regulatory patterns along the trajectory.
Published Open-Access
yes
Recommended Citation
Chaozhong Liu, Linhua Wang, and Zhandong Liu, "Quantification and Visualization of Cis-Regulatory Dynamics in Single-Cell Multi-Omics Data With TREASMO" (2024). Faculty and Staff Publications. 3435.
https://digitalcommons.library.tmc.edu/baylor_docs/3435