Protocol to predict gene expression from transcriptomic data using PREDICT
Journal
STAR Protocols
Journal Volume
7
Journal Issue
2
Start Page
104482
ISSN
2666-1667
Date Issued
2026-06-19
Author(s)
Abstract
Linking DNA sequence variation to context-specific transcriptional programs is a critical challenge in regulatory genomics, especially for non-model organisms. Here, we present PREDICT, a modular Python package for discovering cis -regulatory elements and transcription factor binding motifs. We describe steps to identify enriched k -mers from differentially expressed genes, map them to known motifs, quantify their impact on gene expression, and visualize motif co-occurrences. PREDICT provides a robust, k -mer-based approach to uncover regulatory logic in diverse genomic systems. For complete details on the use and execution of this protocol, please refer to Yen et al. and Liu et al.
Publisher
Elsevier BV
Type
journal article