Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data.

ABSTRACT:

Motivation

In recent years, many algorithms for inferring gene regulatory networks from single-cell transcriptomic data have been published. Several studies have evaluated their accuracy in estimating the presence of an interaction between pairs of genes. However, these benchmarking analyses do not quantify the algorithms' ability to capture structural properties of networks, which are fundamental, e.g., for studying the robustness of a gene network to external perturbations. Here, we devise a three-step benchmarking pipeline called STREAMLINE that quantifies the ability of algorithms to capture topological properties of networks and identify hubs.

Results

To this aim, we use data simulated from different types of networks as well as experimental data from three different or

SUBMITTER: Stock M 

PROVIDER: S-EPMC11096270 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature