Gene Expression Plots

Gene Expression Plots visualizes and analyzes transcriptome data from RNA-Seq to summarize gene expression patterns and support interpretation alongside metabolomics data.

Key Features:

• Supported data types: Supports analysis of RNA-Seq-derived transcriptome data and associated metabolomics datasets.
• Interactive visualization: Generates interactive plots that summarize gene expression and genetic responses.
• MapMan integration: Integrates MapMan to map gene expression data onto biological pathways and processes.
• Cluster and principal component analysis: Performs cluster analysis and principal component analysis for pattern detection and dimensionality reduction.
• Overrepresentation analysis: Performs overrepresentation analysis to detect functional enrichment of gene sets.

Scientific Applications:

• Transcriptomics analysis: Characterizing gene expression patterns across samples or conditions using RNA-Seq data.
• Metabolomics integration: Investigating metabolic responses by integrating gene expression with metabolomics data.
• Pathway-level interpretation: Mapping expression changes onto pathways and processes using MapMan to infer biological significance.
• Sample and gene grouping: Identifying sample groups and gene modules via clustering and principal component analysis.

Methodology:

Transforms raw RNA-Seq and metabolomics data into interpretable outputs via interactive visualizations and statistical analyses, including cluster analysis, principal component analysis, overrepresentation analysis, and MapMan-based pathway mapping.