SignifiKANTE: Efficient P-value computation for gene regulatory networks

Woller F, Martini P, Sen S, Blumenthal DB, Hartebrodt A (2026)

Publication Type: Journal article

Publication year: 2026

Journal

Original Authors: Fabian Woller, Paul Martini, Souptik Sen, David B Blumenthal, Anne Hartebrodt

Article Number: btag531

DOI: 10.1093/bioinformatics/btag531

Abstract

Motivation

Gene regulatory networks (GRNs) are graph-based representations of regulatory relationships between transcription factors and target genes. Various tools exist to infer GRNs from gene expression data, but since GRN inference itself is already computationally intensive, statistical significance estimates are often omitted. While naïve permutation-based empirical P-value computation methods are relatively straightforward to implement, they are prohibitively expensive when applied to popular regression-based GRN inference methods and realistically sized datasets.

Results

To address this bottleneck, we developed SignifiKANTE, a tool to efficiently quantify edge significance in GRNs obtained via any regression-based GRN inference method. SignifiKANTE is based on the key insight that the background count distributions of groups of target genes may be highly similar, even if their expression vectors show distinct behavior. Relying on this insight, SignifiKANTE employs gene clustering based on the 1-Wasserstein distance to create a small, constant number of background distributions which enables the simultaneous computation of approximate permutation-based P-values for multiple target genes. This reduces the runtime by orders of magnitudes (for some datasets, from several weeks to few hours), without compromising faithfulness of the obtained P-values.

Availability and implementation

SignifiKANTE’s Python source code is available at https://github.com/bionetslab/SignifiKANTE, a packaged version at https://pypi.org/project/signifikante, and scripts to reproduce the results at https://github.com/bionetslab/SignifiKANTE_Results.

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How to cite

APA:

Woller, F., Martini, P., Sen, S., Blumenthal, D.B., & Hartebrodt, A. (2026). SignifiKANTE: Efficient P-value computation for gene regulatory networks. Bioinformatics (Oxford, England). https://doi.org/10.1093/bioinformatics/btag531

MLA:

Woller, Fabian, et al. "SignifiKANTE: Efficient P-value computation for gene regulatory networks." Bioinformatics (Oxford, England) (2026).

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