Ningxiang Pig Proteomic Network Analysis for Carcass Trait Regulation

A complete R workflow for weighted co-abundance network analysis of proteomic data from Ningxiang pigs. The repository, authored by Lihua Cao and last updated in April 2026, identifies key protein modules associated with carcass trait regulation. The 13.2 KB resource includes adjacency matrices and edge lists for network visualization.

Use Cases

• Identifying hub proteins regulating carcass traits based on the described co-abundance network analysis.
• Reproducing module-trait association analyses using the provided R workflow and parameters.
• Visualizing protein interaction networks in tools like Cytoscape based on the output adjacency matrices and edge lists.

Strengths

• The analysis pipeline is fully documented with specific parameters like soft-threshold power=6 and minModuleSize=20.
• Outputs include adjacency matrices and edge lists for external network visualization tools.
• The workflow is shared under a permissive CC-BY-4.0 license.

Limitations

• The dataset is very small at 13.2 KB, containing analysis code rather than primary proteomic data.
• Column-level documentation for the underlying proteomic data is absent; field semantics must be inferred after download.
• Row count for the original proteomic data is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Weighted co-abundance network analysis (WGCNA) of proteomic data.

Freshness

Last updated 2026-04-21 08:08:53; freshness should be verified.