scRNA-seq analysis of biopsy tissue from Interstitial Lung Disease patients who took EGCG
Single-cell RNA-seq · human · 10 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 4 × Control Biopsy vs 4 × EGCG BiopsyGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- A fibroblast-dependent TGF-β1/sFRP2 noncanonical Wnt signaling axis promotes epithelial metaplasia in idiopathic pulmonary fibrosisThe Journal of clinical investigation · 2024
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE239664_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1000503 and SRA study SRP452440. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 8 samples.
How we read this: 2 replicated groups read from 10 sample titles; they account for 8 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7669637 Control Biopsy 1 Control Biopsy
- GSM7669638 Control Biopsy 2 Control Biopsy
- GSM7669639 EGCG Biopsy 1 EGCG Biopsy
- GSM7669640 EGCG Biopsy 2 EGCG Biopsy
- GSM7669641 EGCG Biopsy 3 EGCG Biopsy
- GSM7669642 Control Biopsy 3 Control Biopsy
- GSM7669643 Control Biopsy 4 Control Biopsy
- GSM7669644 EGCG Biopsy 4 EGCG Biopsy
- GSM7669645 Normal Donor 1
- GSM7669646 IPF Explant 1
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- GSE309392 Cancer-associated fibroblasts promote esophageal carcinogenesis and lung metastasis by CDH11-mediated extracellular matrix environment remodeling [scRNA-Seq] 23 samples shares scrna-seq, lung
- GSE189357 Spatiotemporal transcriptional atlas of lung adenocarcinoma from adenocarcinoma in situ to invasive carcinoma [scRNA-seq] 9 samples shares scrna-seq, lung
- GSE296912 scRNA-seq of normal and COPD lungs 7 samples shares scrna-seq, lung
- GSE317068 Multiscale analysis and functional validation of the cellular and genetic determinants of skeletal disease [Human scRNA-seq] 32 samples shares scrna-seq
- GSE256490 Single-cell atlas of the human brain vasculature across development, adulthood and disease (scRNA-Seq) 71 samples shares scrna-seq
- GSE292130 Longitudinal changes in DNA methylation in IDH-mutant glioma fuel disease progression through altered cell state differentiation [scRNA-seq] 31 samples shares scrna-seq
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.