iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data

Area of Science:

• Bioinformatics
• Genomics
• Molecular Biology

Background:

• RNA sequencing (RNA-seq) is a powerful tool for transcriptomic profiling.
• Bioinformatic analysis of RNA-seq data is often complex and time-consuming for biologists.
• There is a need for user-friendly tools to simplify RNA-seq data analysis.

Purpose of the Study:

• To develop a user-friendly, interactive web application for streamlining transcriptomic data analysis.
• To facilitate exploratory data analysis, differential gene expression, and pathway analysis.
• To enable biologists to easily translate transcriptomic and proteomic data into actionable insights.

Main Methods:

• Development of the iDEP (integrated Differential Expression and Pathway analysis) web application.
• Integration of 63 R/Bioconductor packages, 2 web services, and extensive annotation/pathway databases.
• Customizable R code and pathway files for workflow reproducibility.

Main Results:

• iDEP supports 220 plant and animal species.
• Analysis of lung fibroblast RNA-seq data revealed roles of SP1, E2F1, and microRNAs in cell cycle regulation.
• Analysis of mouse B cells demonstrated p53's role in apoptosis and DNA repair, contrasting with MYC and E2F1 pathway activation in p53-deficient cells.

Conclusions:

• iDEP integrates comprehensive analytical functionalities with extensive annotation databases.
• The application empowers biologists to readily interpret transcriptomic and proteomic data.
• iDEP facilitates the generation of novel, testable hypotheses from complex biological datasets.