Home Gene query Cohorts & datasets Treatment response Data downloads Pathway query Methods & limitations EN | 中文 PolypAtlas — CRSwNP Multi-omics Resource Data downloads Research use only : This site is an integrated query resource for publicly available chronic rhinosinusitis with nasal polyps (CRSwNP) transcriptomic data, for research reference only. It does not provide clinical diagnosis, disease probability estimates, or treatment recommendations. All values come from uniform reanalysis of public data; known limitations of each cohort are annotated alongside the data.
evidence_matrix_logFC.csv — Bulk: logFC of 19,266 protein-coding genes × 16 cohorts (primary contrasts; probes collapsed by min-p). evidence_matrix_FDR.csv — Bulk: BH-FDR for the same matrix. de_tables.zip — Bulk: full per-cohort differential results for 30 contrasts (symbol, logFC, p, FDR). runlog.csv — Bulk: record of n, scale verdicts, methods and status for 30 contrasts. controls_panel.csv — Bulk: per-cohort values of the 8-gene positive-control panel (CLC/CCL26/CCL13/IL33/TSLP/POSTN/SERPINB2/ALOX15). celltype_evidence_matrix.csv — Single-cell: 17,631 genes × 41 cell-type-level pseudobulk contrasts (logFC+FDR). composition_all.csv — Single-cell: composition table of 1,431 rows (dataset × donor × group × cell type × fraction). alignment_table.csv — Spatial: 1,480 panel genes × 39 columns (two spatial compartments + 16 bulk cohorts + same-study single-cell averages). roi_metadata.csv — Spatial: 40-ROI metadata (including QC flag GSM7508390). curation_table.csv — Master curation table: per-series grading of all 66 series (verdict / evidence notes). enrichment_ora.csv — Analysis layer: over-representation enrichment for all contrasts (GO BP/CC/MF, Reactome, KEGG; up/down separately; low-DE directions skipped). enrichment_gsea.csv — Analysis layer: GSEA for 62 adequately powered contrasts (Hallmark, GO-BP, Reactome, KEGG; 40 MB). program_scores.csv — Analysis layer: per-sample ssGSEA program scores (13 programs × 16 bulk cohorts). program_summary.csv — Analysis layer: per-cohort program case-vs-control summary. deconv_scores.csv — Analysis layer: per-sample immune abundance estimates (MCP-counter-style marker scoring). deconv_summary.csv — Analysis layer: per-cohort deconvolution group summary. consensus_annotated.csv — Consensus genes (disease-only, 825 up / 196 down) with known approved-drug target annotation. consensus_enrichment.csv — Consensus genes: pathway enrichment of the up/down lists. lr_interactions_CRSwNP_vs_control.csv — Cell–cell communication (CellChat, GSE235711): CRSwNP vs control interaction comparison. lr_interactions_CRSsNP_vs_control.csv — Cell–cell communication (CellChat, GSE235711): CRSsNP vs control interaction comparison. meta_combined.csv — Meta-analysis: per-gene combined logFC, 95% CI, combined p, I², k (DerSimonian–Laird, 10 primary contrasts; genes with k≥3). meta_percohort.csv — Meta-analysis: per-cohort logFC and SE for the same genes (forest-plot input). drug_reversal_l1000cds2.csv — Drug reversal: L1000CDS2 hits for the consensus signature (top 50; in-silico hypothesis generation only). genetic_support.csv — Genetic support: GWAS Catalog p≤5e-8 hits and GTEx v8 eQTL presence per gene (proxy tissues noted). coexpression_top10.csv — Co-expression: top-10 positive partners per gene (Fisher-z averaged Spearman over ≥3 bulk cohorts). literature_support.csv — Literature support: per-gene claim counts from the original-paper reproduction audit (audited genes only). treatment_response.json — Treatment response: GSE267331 dupilumab stats, marker reversal, program changes, contrast inventory (JSON). Usage notes : all files are products of uniform reanalysis; each file’s generation protocol is on the ‘Methods & limitations’ page; annotated h5ad objects are too large to host here (available from the authors on request).