TRIAGE Toolkit: Streamlined Discovery of Regulatory Genes and Elements

Abstract

Efficient discovery of regulatory genes and elements is essential for understanding cell identity, differentiation, and disease mechanisms. The TRIAGE methods are a set of well‐established computational approaches that identify context‐specific regulatory genes and prioritize regulatory elements across the genome. Previous publications have described the development of these algorithms, their benchmarking, and biological applications. Here, we provide step‐by‐step protocols for applying the TRIAGE methods to identify regulatory drivers from diverse input types, including gene expression matrices, gene lists, and genomic loci. It covers analyses of both bulk and single‐cell RNA‐seq datasets and enables genome‐wide interrogation of regulatory elements at single‐base resolution. The analysis is efficient, typically requiring <30 min of computation time on a personal computer. In addition to the step‐by‐step description of the TRIAGE analysis workflow, we provide the TRIAGE toolkit, available as both an R package and a Python implementation, to support flexible and scalable regulatory analysis across platforms. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1 : Prioritization of regulatory genes from bulk RNA‐seq data

Basic Protocol 2 : Identification of cell populations and regulatory genes in single‐cell RNA‐seq data

Basic Protocol 3 : Prioritization of regulatory long noncoding RNAs

Basic Protocol 4 : Prioritization of functional genetic variants from eQTL data

Alternate Protocol : Python‐based implementation of the TRIAGE workflow for regulatory gene and element prioritization

Support Protocol : Preparing a normalized expression matrix from bulk RNA‐seq count data