Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens [scRNA-seq]
Single-cell RNA-seq · mouse · 10 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 10 samples: 5 conditions, mostly in duplicateGroups 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.
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 GSE261783_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 PRJNA1088862 and SRA study SRP495953. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 5 replicated groups read from 10 sample titles; they account for 10 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.
- GSM8151750 Activated_OP1L_NM_NA_Rep1 Activated_OP1L_NM_NA
- GSM8151751 Activated_OP1L_NM_NA_Rep2 Activated_OP1L_NM_NA
- GSM8151752 Quiescent_OP1L_NM_NA_Rep1 Quiescent_OP1L_NM_NA
- GSM8151753 Quiescent_OP1L_NM_NA_Rep2 Quiescent_OP1L_NM_NA
- GSM8151754 exVivo_OP2_IL1b_1 exVivo_OP2_IL1b
- GSM8151755 exVivo_OP2_IL1b_2 exVivo_OP2_IL1b
- GSM8151756 exVivo_OP2_resting_1 exVivo_OP2_resting
- GSM8151757 exVivo_OP2_resting_2 exVivo_OP2_resting
- GSM8151758 exVivo_OP2_TGFb_1 exVivo_OP2_TGFb
- GSM8151759 exVivo_OP2_TGFb_2 exVivo_OP2_TGFb
- GSE227108 Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells (scRNA-seq) 18 samples shares single-cell, epigenetic, scrna-seq
- GSE334890 Discovery of Tcf7 regulators with clonally-resolved CRISPR screens identifies Trim28 as a mediator of CD8 T cell differentiation in tumors 48 samples shares crispr, regulators
- GSE300288 Single-cell and spatial transcriptomics analysis of tobacco-associated lung adenocarcinoma development, and in response to targeting inflammation alone or in combination with immune checkpoint blockade in precancerous phase [scRNA-seq] 31 samples shares single-cell, scrna-seq
- GSE264607 Molecular targets of colorectal cancer transformation revealed by single-cell sequencing 14 samples shares transformation, single-cell
- GSE303460 Spatiotemporal single-cell atlas of suture stem cell dynamics in craniosynostosis [scRNA-Seq] 14 samples shares single-cell, scrna-seq
- GSE313761 Single-cell screens identify ADAM12 as a fibroblast checkpoint impeding anti-tumor immunity - scRNA-seq of Adam12CKO Mouse Model CD45- cells 11 samples shares single-cell, scrna-seq
- GSE220675 Kidney Single-Cell Atlas Reveals Macrophage Heterogeneity in Progression and Regression of Cisplatin Induced AKI [scRNA-seq] 11 samples shares single-cell, scrna-seq
- GSE329635 Single-cell RNA sequencing of small intestinal organoid self-organization [scRNA-Seq] 10 samples shares single-cell, 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.