Parallel single-cell bisulfite- and RNA-sequencing link transcriptional and epigenetic heterogeneity [RNA-seq]
Single-cell RNA-seq · mouse · 96 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
- 96 samples: 96 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.
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 GSE74534_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 PRJNA300667 and SRA study SRP065548. 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 96 sample titles: 96 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.
- GSM1922258 Serum_A01 [RNA-seq]
- GSM1922259 Serum_A02 [RNA-seq]
- GSM1922260 Serum_A03 [RNA-seq]
- GSM1922261 Serum_A04 [RNA-seq]
- GSM1922262 Serum_A05 [RNA-seq]
- GSM1922263 Serum_A06 [RNA-seq]
- GSM1922264 Serum_A07 [RNA-seq]
- GSM1922265 Serum_A08 [RNA-seq]
- GSM1922266 Serum_A09 [RNA-seq]
- GSM1922267 Serum_A10 [RNA-seq]
- GSM1922268 2i_A11 [RNA-seq]
- GSM1922269 2i_A12 [RNA-seq]
- GSM1922270 Serum_B01 [RNA-seq]
- GSM1922271 Serum_B02 [RNA-seq]
- GSM1922272 Serum_B03 [RNA-seq]
- GSM1922273 Serum_B04 [RNA-seq]
- GSM1922274 Serum_B05 [RNA-seq]
- GSM1922275 Serum_B06 [RNA-seq]
- GSM1922276 Serum_B07 [RNA-seq]
- GSM1922277 Serum_B08 [RNA-seq]
- GSM1922278 Serum_B09 [RNA-seq]
- GSM1922279 Serum_B10 [RNA-seq]
- GSM1922280 2i_B11 [RNA-seq]
- GSM1922281 2i_B12 [RNA-seq]
- GSM1922282 Serum_C01 [RNA-seq]
- GSM1922283 Serum_C02 [RNA-seq]
- GSM1922284 Serum_C03 [RNA-seq]
- GSM1922285 Serum_C04 [RNA-seq]
- GSM1922286 Serum_C05 [RNA-seq]
- GSM1922287 Serum_C06 [RNA-seq]
- GSM1922288 Serum_C07 [RNA-seq]
- GSM1922289 Serum_C08 [RNA-seq]
- GSM1922290 Serum_C09 [RNA-seq]
- GSM1922291 Serum_C10 [RNA-seq]
- GSM1922292 2i_C11 [RNA-seq]
- GSM1922293 2i_C12 [RNA-seq]
- GSM1922294 Serum_D01 [RNA-seq]
- GSM1922295 Serum_D02 [RNA-seq]
- GSM1922296 Serum_D03 [RNA-seq]
- GSM1922297 Serum_D04 [RNA-seq]
+ 56 more — browse all 96 samples with per-sample file links →
- GSE243942 Spatio-temporal X-linked gene reactivation in the mouse germline reveals site-specific retention of epigenetic silencing [RNA-seq] 125 samples shares epigenetic, rna-seq, link
- GSE262879 Single-cell RNA-sequencing of murine pancreatic tumors derived from the orthotopic transplantation of Smad4 wild-type (WT) or Smad4 knockout (KO) pancreatic ductal adenocarcinoma (PDAC) KPC organoids in nu/nu mice. 18 samples shares rna-sequencing, single-cell, rna-seq
- GSE227108 Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells (scRNA-seq) 18 samples shares single-cell, epigenetic, rna-seq
- GSE297298 Single-cell RNA-sequencing identifies anti-cancer immune phenotypes in the early lung metastatic niche during breast cancer 18 samples shares rna-sequencing, single-cell, rna-seq
- GSE220675 Kidney Single-Cell Atlas Reveals Macrophage Heterogeneity in Progression and Regression of Cisplatin Induced AKI [scRNA-seq] 11 samples shares heterogeneity, single-cell, rna-seq
- GSE308939 Single-cell RNA-seq reveals the keratinocyte heterogeneity and increased interfollicular basal keratinocytes in wound-induced hair follicle neogenesis 6 samples shares heterogeneity, single-cell, rna-seq
- GSE277789 Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq-add] 830 samples shares single-cell, rna-seq
- GSE269748 A single-cell atlas deconstructs heterogeneity across multiple models in murine traumatic brain injury and identifies novel cell-specific targets 36 samples shares heterogeneity, 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.