Multi-Omics Analysis of Osteoarthritis Synovial Tissue Identifying MSR1 Gene

517 genes associated with osteoarthritis were identified through RNA-seq analysis of synovial tissue from the GEO databases. The dataset includes results from weighted gene co-expression network analysis (WGCNA), differential expression analysis, and protein-protein interaction networks, identifying MSR1 as a key candidate. Author Jinquan Bao published this 46.6 KB Excel file on figshare in May 2026 under a CC-BY-4.0 license.

Use Cases

• Validate MSR1 gene expression differences between osteoarthritis and healthy samples based on differential expression analysis.
• Investigate immune modulation in osteoarthritis pathogenesis based on correlations between MSR1 expression and immune populations.
• Screen for potential drug candidates targeting MSR1 based on molecular docking results identifying hesperidin.
• Study the interplay between programmed cell death and extracellular matrix in inflammatory diseases based on the identified 24 related genes.

Strengths

• Analysis is based on RNA-seq data from a public repository (GEO databases).
• The study used both training and validation sets, with MSR1 showing an AUC value greater than 0.7.
• Integrative approach combines multiple bioinformatics methods (WGCNA, differential expression, PPI network).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset's 46.6 KB size suggests a limited scope, likely containing summary results rather than raw sequence data.

Provenance

Source

RNA-seq data from GEO databases, analyzed by author Jinquan Bao.

Collection Method

Bioinformatics analysis including WGCNA, differential expression analysis, cross analysis, and PPI network construction.

Freshness

Last updated 2026-05-21 04:35:57; freshness should be verified.