Expression Atlas

Expression Atlas provides a curated resource for exploring gene and protein expression across species, tissues, cell types, developmental stages and diseases using processed microarray, RNA-sequencing and proteomics datasets.

Key Features:

• Data types and sources: Aggregates microarray, RNA-sequencing and proteomics datasets sourced from ArrayExpress and large projects including the Human Protein Atlas, GTEx, FANTOM5, ENCODE, CCLE and Genentech.
• Baseline expression profiles: Provides baseline expression profiles derived from projects such as Human Protein Atlas, GTEx and FANTOM5 for human tissues and ENCODE, CCLE and Genentech for cell lines.
• Differential expression via pairwise comparisons: Performs differential expression analyses using biologically meaningful pairwise comparisons with consistent methodologies across datasets.
• Manual curation and ontology annotation: Curates studies manually and annotates experimental conditions with relevant ontology terms.
• Quality assurance and standardized analysis: Applies quality assurance checks and standardized analysis methods to microarray and RNA-seq studies.
• Proteomics–transcriptomics integration: Integrates proteomics data with transcriptomics data from the same biological samples.
• Enrichment analysis: Computes enrichment for Gene Ontology (GO) terms, Reactome pathways, Plant Reactome pathways and InterPro domains in differential comparisons.
• Hierarchical clustering: Performs hierarchical clustering of genes based on baseline expression across experimental conditions.
• Expression distribution visualization: Provides distribution views of baseline expression across biological replicates for specific gene–condition pairs.
• Plant study representation: Includes a substantial proportion of plant studies, representing about one-quarter of the dataset.

Scientific Applications:

• Baseline expression mapping: Characterizes tissue- and cell type–specific baseline expression across human and other species.
• Differential expression analysis: Identifies genes differentially expressed between biological conditions and disease states using pairwise comparisons.
• Proteogenomic integration: Enables combined analysis of proteomics and transcriptomics in the same samples to study molecular concordance.
• Functional and pathway interpretation: Facilitates interpretation of differential expression via GO, Reactome, Plant Reactome and InterPro enrichment.
• Pattern discovery: Detects gene expression patterns and variability across conditions using hierarchical clustering and distribution analyses.

Methodology:

Studies undergo manual curation, annotation with ontology terms, quality assurance checks and standardized analysis methods applied to microarray and RNA-sequencing data; differential expression is computed via biologically meaningful pairwise comparisons, with downstream enrichment analysis (GO, Reactome, Plant Reactome, InterPro), hierarchical clustering of baseline expression and distribution visualizations, and integration of proteomics with transcriptomics where available.