Congratulations to our group members, Haiyi Mao and Minxue Jia, for their paper accepted in Nature Communications. Their paper is entitled “HALO: Hierarchical Causal Modeling for Single Cell Multi-Omics Data”.
This paper presents a novel method, HALO, to model multi-omits single cell data (scRNAseq and scATACseq measured concurrently). HALO adopts a causal approach to model DNA-gene interactions as “coupled” (when chromatin status and gene expression are in sync) and “decoupled”. HALO was tested in simulated data and multiple real-life datasets (including lung epithelial cells in SSc-ILD). HALO is a versatile tool that can be used to identify distal cis-regulatory interactions and reveal new critical disease mechanisms.
In this study, Marissa Di, another group member, contributed. We are also grateful to Drs. Kun Zhang, Eleanor Valenzi, and Bob Lafyatis for their help in strengthen this paper.
Paper availability: [journal web site] [bioRxiv]
Software availability: https://github.com/benoslab/HALO
Congratulations to Haiyi and Minxue for this great paper!
