Data Sheet 3_Geometric multidimensional representation of omic signatures.zip

24,796 metabolic regulatory circuitries reconstructed across 32 TCGA cancer types are represented as convex polytopes in an 18-dimensional latent space. The dataset includes geometric descriptors like barycenter distance, volume, anisotropy, and asymmetry, quantifying concordance and complexity in multi-omic signatures. It was created by Higor Almeida Cordeiro Nogueira and last updated on 2026-04-17.

Use Cases

• Stratifying metabolic pathways and superfamilies based on geometric phenotypes like asymmetry and anisotropy.
• Comparing and de-redundanting multi-omic biomarkers using intrinsic geometric measurements.
• Analyzing complex regulatory systems across cancer types using a geometric framework.

Strengths

• Includes 24,796 metabolic regulatory circuitries, providing a substantial scale for analysis.
• Covers 32 distinct TCGA cancer types, enabling cross-cancer comparisons.
• Data is available through an interactive Shiny application for exploration.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying signature data is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Geometric framework applied to reconstructed metabolic circuitries from TCGA data.

Freshness

Last updated 2026-04-17 05:22:14; freshness should be verified.