TEnGExA

TEnGExA performs tissue-enrichment analysis of gene expression data to classify transcripts across multiple tissues and species for downstream interpretation of RNA-seq studies.

Key Features:

• Versatility Across Species: Processes gene expression data from humans, plants, and microorganisms.
• Input Flexibility: Accepts read-count and FPKM-value matrices as input.
• Threshold-Based Classification: Uses customizable FPKM value and fold-change thresholds to classify genes into categories such as tissue-enriched or tissue-specific transcripts.
• Scalability: Handles any number of genes or tissues and processes large RNA-seq datasets efficiently.
• Transcript-Type Classification: Classifies transcript types including coding sequences (CDS), alternative splicing variants, circular RNAs, and long non-coding RNAs (lncRNAs).

Scientific Applications:

• Functional Annotation and Pathway Analysis: Relates tissue-specific expression patterns to biological pathways and networks for functional interpretation.
• Transcript Categorization: Enables categorization of CDS, alternative splicing variants, circular RNAs, and lncRNAs into tissue-enrichment categories.
• Multi-tissue Comparative Analysis: Supports comparative analysis across multiple tissues to identify tissue-specific and tissue-enriched expression patterns.

Methodology:

Analyzes RNA-seq data by processing read-count or FPKM matrices to determine gene expression patterns across tissues and classifies genes based on user-defined FPKM and fold-change thresholds.