ULMnet: inferring physical cell-cell communication networks from scRNAseq data using univariate linear models.

ABSTRACT:

Introduction

Cells in tissues interact by direct physical contact or over short and long distances via secreted mediators. Cell-cell communication inference has now become routine in downstream scRNAseq analysis but this mostly fails to capture physical cell-cell interactions due to tissue dissociation. Multiplets (mostly doublets) in scRNAseq may represent undissociated physically attached cells that become sequenced together. Hence, identifying multiplets may serve as a good starting point to harness scRNAseq data for physical cell-cell interaction inference.

Method

In this study, we develop a computational method, called ULMnet, which utilizes univariate linear models to identify multiplets in scRNAseq datasets, predict their cellular compositions, and infer physical cell

SUBMITTER: Hameed SA 

PROVIDER: S-EPMC12827579 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature