Single-cell joint analysis of DNA oxidative damage and transcriptome [bulk damage]
Single-cell RNA-seq · mouse · 12 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
- 12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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
- Single-cell parallel analysis of DNA damage and transcriptome reveals selective genome vulnerabilityNature methods · 2025
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 GSE268552_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 PRJNA1117786 and SRA study SRP510448. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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.
- GSM8294220 Hela_control_bulk_damage
- GSM8294221 Hela_0hr_bulk_damage
- GSM8294222 Hela_2hr_bulk_damage
- GSM8294223 Hela_6hr_bulk_damage
- GSM8294224 Hela_24hr_bulk_damage
- GSM8294225 Hela_48hr_bulk_damage
- GSM8633802 Hela_bulk_nucleosome_depletion
- GSM8633803 Mouse_Cortex_bulk_nucleosome_depletion
- GSM8633804 Hela_prerepair_bulk_damage
- GSM8633805 Hela_5mM_bulk_damage
- GSM8633806 Hela_10mM_bulk_damage
- GSM8633807 Hela_nickase_bulk_damage
- GSE268567 Single-cell parallel analysis of DNA damage and transcriptome reveals selective genome vulnerability 30 samples shares single-cell, damage
- GSE261742 Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens 69 samples shares single-cell, bulk
- GSE249011 Bulk and single-cell RNA sequencing of human and murine eosinophil lineage cells 62 samples shares single-cell, bulk
- GSE246859 ChromaFold predicts the 3D contact map from single-cell chromatin accessibility 3 samples shares single-cell
- GSE202126 Single-cell Total-RNA Profiling Unveils Regulatory Hubs of Transcription Factors 1089 samples shares single-cell
- GSE290486 Matched single-cell chromatin, transcriptome, and surface marker profiling captures in vivo epigenomic reprogramming during basal-to-luminal transition in the mammary gland 37 samples shares single-cell
- GSE272618 Single-Molecule Barcoding Technology for Single-Cell Genomics 140 samples shares single-cell
- GSE266161 RoCK and ROI: a single-cell RNA-sequencing method with enhanced transcriptome information via targeted enrichment of transcripts and preselected, region-specific sequencing 13 samples shares single-cell
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.