Gene Ontology Functional Annotation for Schizophrenia Transcriptomic Analysis

The PsychENCODE consortium generated transcriptomic data from human brain samples. This dataset contains Gene Ontology functional annotation results from a multi-method analysis of schizophrenia-associated gene modules. The 9.5 KB XLS file was authored by Costas Bampos and last updated on April 15, 2026.

Use Cases

• Validate schizophrenia-associated gene modules based on functional enrichment results.
• Compare biological signatures from different network analysis methods (igraph, WGCNA, PCA).
• Investigate immune, synaptic, and epigenetic processes in schizophrenia based on pathway enrichment.
• Identify hub genes involved in mRNA export, synaptic signaling, and ion transport based on centrality measures.

Strengths

• Data is derived from the PsychENCODE consortium's multi-omic dataset.
• Analysis applied three independent methods (igraph, WGCNA, PCA) to the same underlying data.
• Functional enrichment was performed using Gene Ontology (GO) and KEGG pathway databases.
• Dataset is openly licensed under CC-BY-4.0.

Limitations

• Dataset is very small at 9.5 KB, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

PsychENCODE consortium transcriptomic data, analyzed by Costas Bampos.

Collection Method

Analysis of gene co-expression and regulatory networks using Surrogate Variable Analysis (SVA), Pearson correlation, igraph, WGCNA, and PCA.

Freshness

Last updated 2026-04-15 17:47:14; freshness should be verified.