Congratulations to our group members, Haiyi Mao, Minxue Jia, and Marissa Di 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.
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, Minxue, and Marissa for this great paper!
