TEnGExA: an R package based tool for tissue enrichment and gene expression analysis

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• High-throughput sequencing generates vast RNA-seq data, enabling transcriptomic analysis.
• Tissue-specific or enriched transcripts are crucial for downstream analysis of multi-tissue data.
• Existing tools lack efficiency in performing tissue-enrichment analysis across diverse datasets.

Purpose of the Study:

• To develop a rapid and user-friendly tool for tissue-enrichment analysis (TEA).
• To enable identification of tissue-specific and enriched transcripts from RNA-seq data.
• To provide a solution for analyzing large and complex multi-tissue transcriptomic datasets.

Main Methods:

• Development of an R package and a web interface tool named TEnGExA.
• Inputting read-count or fragments per kilobase of transcript per million fragments mapped (FPKM) value matrices.
• Classification of genes based on FPKM values and fold thresholds for tissue-enrichment and specificity.

Main Results:

• TEnGExA successfully performs tissue-enrichment analysis for any number of genes or tissues across species.
• The tool efficiently handles large and complex datasets, classifying transcripts into various categories.
• Analysis of human, plant, and microorganism data demonstrates TEnGExA's broad applicability and speed.

Conclusions:

• TEnGExA is a quick, user-friendly, and efficient tool for tissue-enrichment analysis.
• The R package and web interface facilitate downstream analysis of tissue-specific and enriched transcripts.
• TEnGExA supports diverse species and data types, making it valuable for transcriptomic research.