KEGG Pathway Enrichment Results from PsychENCODE Schizophrenia Transcriptomics

KEGG pathway enrichment results derived from a multi-omic analysis of human brain samples by the PsychENCODE consortium. The 5.5 KB XLS file contains results from three analytical approaches applied to transcriptomic data from individuals with schizophrenia and healthy controls. The dataset was authored by Costas Bampos and last updated on April 15, 2026.

Use Cases

• Validate and compare gene enrichment signatures from different network analysis methods based on the described igraph, WGCNA, and PCA approaches.
• Investigate the role of immune, synaptic, and epigenetic pathways in schizophrenia based on the functional enrichment results mentioned.
• Identify potential hub genes for further study based on centrality measures from the described graph-based analysis.
• Benchmark new pathway analysis tools against results from established methods like WGCNA and SVA-corrected data.

Strengths

• Results are derived from the PsychENCODE consortium's multi-omic dataset, a recognized resource in neuropsychiatric research.
• Analysis applied three independent methods (igraph-based, WGCNA, PCA) to the same data, suggesting a multi-faceted validation approach.
• Dataset is openly shared under a CC-BY-4.0 license, facilitating reuse.

Limitations

• The dataset is very small at 5.5 KB, indicating it contains summary results rather than raw or intermediate analysis data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain statistical reviews.

Provenance

Source

PsychENCODE consortium data, analyzed by Costas Bampos.

Collection Method

Computational analysis of transcriptomic data using Surrogate Variable Analysis (SVA), gene co-expression networks (igraph, WGCNA), and dimensionality reduction (PCA, t-SNE, MDS).

Freshness

Last updated 2026-04-15 17:47:18; freshness should be verified.