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Updated: May 28, 2025

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Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
Published on: September 18, 2021
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VIBE: an R-package for VIsualization of Bulk RNA Expression data for therapeutic targeting and disease stratification
Indu Khatri1, Saskia D van Asten1, Leandro F Moreno1
1Translational Data Science, Genmab, Utrecht, Netherlands.
Frontiers in Oncology
|February 13, 2025
Summary
VIBE is a new R package for analyzing gene expression data to aid in developing targeted cancer therapies. It visualizes gene and pathway expression, facilitating disease stratification and drug target identification for personalized medicine.
Area of Science:
- Bioinformatics
- Genomics
- Cancer Research
Background:
- Antibody-based cancer therapies require understanding gene expression and signaling pathways.
- Existing transcriptomic tools lack comprehensive pathway-guided analysis for targeted therapies.
- VIBE (VIsualization of Bulk RNA Expression data) is introduced as a solution.
Purpose of the Study:
- To introduce VIBE, an R package for comprehensive transcriptomic data analysis.
- To enable pathway-guided analysis for single- and dual-targeting cancer therapies.
- To aid in disease stratification and therapeutic target identification.
Main Methods:
- VIBE provides functions for visualizing and analyzing transcriptomic data.
- It allows evaluation of individual gene and pathway expression.
- Incorporates metadata for patient cohort refinement and uses statistics in graphics.
Main Results:
- VIBE streamlines visualization and analysis for targeted therapies.
- Enables evaluation of target genes and associated pathways across cancer indications.
- Demonstrates utility in indication selection and target identification via case studies.
Conclusions:
- VIBE facilitates detailed visualization of gene and pathway expression summaries.
- Prioritizes indications for bispecific or monoclonal antibody therapies.
- Enhances indication selection and accelerates development of novel targeted therapies.
Keywords:
R packageantibodybioinformatics tooldisease stratificationoncologytargeted therapytranscriptomicsvisualizationMore Related Videos
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