Figures and Supplementary Materials for "Integrated Bulk and Single-Cell Transcriptomics Identify a Five-Gene Immune–Endothelial–Matrix Signature in Endometriosis"
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Abstract
This record provides the complete set of publication-quality main figures and supplementary materials accompanying the manuscript above. The study integrates two GEO microarray cohorts (GSE23339, GSE25628) with WGCNA, differential expression, and PPI topology; combines LASSO + Random Forest + ANN to derive a compact five-gene panel (BGN, CXCL12, SERPINF1, TIMP2, SELE); profiles the immune landscape via CIBERSORT; anchors signals to cell states using an independent single-cell atlas (GSE247695); runs gene-stratified GSEA; explores GWAS–eQTL colocalization (FinnGen/GTEx v8); and performs DSigDB-guided docking and 100-ns MD for early translational prioritization. The results support an immune–endothelial–matrix axis as a tractable core of endometriosis biology and diagnostics. Contents Figures: All main figures (numbering matches the manuscript). Supplementary: Tables S1–S16 (CSV/XLSX): DEG lists; WGCNA modules/overlaps; enrichment outputs (GO/KEGG/DO); PPI hubs; ML feature sets; ROC/AUC metrics; immune-infiltration results; single-cell summaries; GSEA outputs; TF–miRNA–lncRNA network tables; colocalization statistics; DSigDB results; docking/MD summaries. Figures S1–S9: Extended analyses/quality controls. Readme: File inventory and variable descriptions. Note: This deposit aggregates derived figures and supplementary tables supporting the manuscript’s findings; primary datasets remain hosted by third-party repositories listed below. Primary public data sources NCBI GEO: GSE23339, GSE25628 (bulk microarrays) and GSE247695 (single-cell RNA-seq) — https://www.ncbi.nlm.nih.gov/geo/ FinnGen: Endometriosis GWAS summary statistics, phenocode N14,Endometriosis — https://www.finngen.fi/ GTEx v8: Cross-tissue cis-eQTLs — https://www.gtexportal.org/ RCSB PDB: Protein structures — https://www.rcsb.org/ PubChem: Compound records — https://pubchem.ncbi.nlm.nih.gov/ DSigDB: Drug–gene signature database — https://dsigdb.genesigdb.org/
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Figures and Supplementary Materials for "Integrated Bulk and Single-Cell Transcriptomics Identify a Five-Gene Immune–Endothelial–Matrix Signature in Endometriosis"
Authors/Creators
Description
This record provides the complete set of publication-quality main figures and supplementary materials accompanying the manuscript above. The study integrates two GEO microarray cohorts (GSE23339, GSE25628) with WGCNA, differential expression, and PPI topology; combines LASSO + Random Forest + ANN to derive a compact five-gene panel (BGN, CXCL12, SERPINF1, TIMP2, SELE); profiles the immune landscape via CIBERSORT; anchors signals to cell states using an independent single-cell atlas (GSE247695); runs gene-stratified GSEA; explores GWAS–eQTL colocalization (FinnGen/GTEx v8); and performs DSigDB-guided docking and 100-ns MD for early translational prioritization. The results support an immune–endothelial–matrix axis as a tractable core of endometriosis biology and diagnostics.
Contents
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Figures: All main figures (numbering matches the manuscript).
-
Supplementary:
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Tables S1–S16 (CSV/XLSX): DEG lists; WGCNA modules/overlaps; enrichment outputs (GO/KEGG/DO); PPI hubs; ML feature sets; ROC/AUC metrics; immune-infiltration results; single-cell summaries; GSEA outputs; TF–miRNA–lncRNA network tables; colocalization statistics; DSigDB results; docking/MD summaries.
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Figures S1–S9: Extended analyses/quality controls.
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Readme: File inventory and variable descriptions.
-
Note: This deposit aggregates derived figures and supplementary tables supporting the manuscript’s findings; primary datasets remain hosted by third-party repositories listed below.
Primary public data sources
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NCBI GEO: GSE23339, GSE25628 (bulk microarrays) and GSE247695 (single-cell RNA-seq) — https://www.ncbi.nlm.nih.gov/geo/
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FinnGen: Endometriosis GWAS summary statistics, phenocode N14,Endometriosis — https://www.finngen.fi/
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GTEx v8: Cross-tissue cis-eQTLs — https://www.gtexportal.org/
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RCSB PDB: Protein structures — https://www.rcsb.org/
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PubChem: Compound records — https://pubchem.ncbi.nlm.nih.gov/
-
DSigDB: Drug–gene signature database — https://dsigdb.genesigdb.org/
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Figure 1.tif
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