Optimized network inference for immune diseased single cells.

ABSTRACT:

Introduction

Mathematical models are powerful tools that can be used to advance our understanding of complex diseases. Autoimmune disorders such as systemic lupus erythematosus (SLE) are highly heterogeneous and require high-resolution mechanistic approaches. In this work, we present ONIDsc, a single-cell regulatory network inference model designed to elucidate immune-related disease mechanisms in SLE.

Methods

ONIDsc enhances SINGE's Generalized Lasso Granger (GLG) causality model used in Single-cell Inference of Networks using Granger ensembles (SINGE) by finding the optimal lambda penalty with cyclical coordinate descent. We benchmarked ONIDsc against existing models and found it consistently outperforms SINGE and other methods when gold standards are generated from chroma

SUBMITTER: Tejero EM 

PROVIDER: S-EPMC12328306 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature