TFNetPropX: A Web-Based Comprehensive Analysis Tool for Exploring Condition-Specific RNA-Seq Data Using Transcription Factor Network Propagation

Understanding condition-specific biological mechanisms from RNA-seq data requires comprehensive analysis of gene expression data, from the gene to the network level. However, this requires computational expertise, which limits the accessibility of data analysis for understanding biological mechanisms. Therefore, the development of an easy-to-use and comprehensive analysis system is essential. In response to this issue, we present TFNetPropX, a user-friendly web-based platform designed to perform gene-level, gene-set-level, and network-level analysis of RNA-seq data under two different conditions. TFNetPropX performs comprehensive analysis, from DEG analysis to network propagation, to predict TF-affected genes with a single request, and provides users with an interactive web-based visualization of the results. To demonstrate the utility of our system, we performed analysis on two TF knockout RNA-seq datasets and effectively reproduced biologically significant findings. We believe that our system will make it easier for biological researchers to gain insights from different perspectives, allowing them to develop diverse hypotheses and analyses.

Automated summary

Comprehensive analysis of gene expression data is essential for understanding condition-specific biological mechanisms from RNA-seq data. However, this often requires computational expertise, limiting accessibility to data analysis. To address this issue, TFNetPropX is introduced as an easy-to-use web-based platform that enables gene-level, gene-set-level, and network-level analysis of RNA-seq data under different conditions. The system predicts TF-affected genes and provides interactive web-based visualization of the results. Analysis on two TF knockout RNA-seq datasets demonstrates the utility of the system.