LRP1 Diagnostic Model for Endometriosis: Multi-Omics and Single-Cell Evidence

A multi-omics analysis dataset supporting a diagnostic model for endometriosis, focusing on the biomarker LRP1. The data was generated by Chengmao Xie and last updated on April 15, 2026. It integrates results from three GEO datasets, identifying 1,404 differentially expressed genes and 30 hub genes through machine learning.

Use Cases

• Validate the diagnostic performance of LRP1 for endometriosis based on identified hub genes.
• Investigate the correlation between LRP1 and M2 macrophage infiltration based on immune profiling results.
• Study cell-cell communication in endometriosis lesions based on single-cell RNA sequencing findings for the MIF signaling pathway.
• Explore causal relationships in endometriosis genetics based on Mendelian randomization analysis results.

Strengths

• Integrates three public GEO datasets (GSE7305, GSE11691, GSE25628) for analysis.
• Identifies 1,404 differentially expressed genes and 30 hub genes, with LRP1 showing the highest diagnostic performance.
• Includes experimental validation showing elevated LRP1 expression at mRNA and protein levels.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• The dataset is very small (9.3 KB), suggesting it contains summary or model results rather than raw sequencing data.

Provenance

Source

figshare, author Chengmao Xie.

Collection Method

Integrated analysis of three GEO datasets using WGCNA and machine learning, supplemented by single-cell RNA sequencing and experimental validation.

Time Range

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Freshness

Last updated 2026-04-15 04:22:12; freshness should be verified.

Geography

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