Multi-omics Mendelian Randomization Data for Mitochondrial Genes in Endometriosis

1,133 mitochondrial-related genes from the MitoCarta3.0 database were analyzed using eQTL, pQTL, and mQTL data from the eQTLGen, DECODE, and Brisbane databases. Two-sample Mendelian randomization and summary data Mendelian randomization were performed using FinnGen endometriosis GWAS data. The dataset was created by Sha Wang and last updated on May 4, 2026.

Use Cases

• Identify causal relationships between mitochondrial genes and endometriosis based on Mendelian randomization results.
• Select feature genes for endometriosis prediction based on machine learning algorithms applied to transcriptomic datasets.
• Assess correlations between mitochondrial gene expression and immune cell infiltration based on single-sample gene set enrichment analysis.

Strengths

• Analysis includes 1,133 mitochondrial-related genes from the MitoCarta3.0 database.
• Mendelian randomization identified 128 mitochondrial genes with significant causal relationships to endometriosis.
• Validation was performed using immunohistochemistry on patient samples, confirming transcriptomic findings for GPD2 and MRPS6.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small at 152.0 KB, indicating limited scope.

Provenance

Source

figshare

Collection Method

Multi-omics bioinformatics analysis incorporating eQTL, pQTL, and mQTL data, Mendelian randomization, and machine learning on transcriptomic datasets.

Freshness

Last updated 2026-05-04 05:30:47; freshness should be verified.