Spatiotemporal Clonal Architecture of the Newborn Mouse Forebrain
Single-cell RNA-seq · mouse · 186 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Mus musculus (mouse)
- Samples
- 186 samples: 186 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 GSE341480_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 PRJNA1502822 and SRA study SRP721645. 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 186 sample titles: 186 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.
- GSM9907397 ST5_L1, Transcriptome library
- GSM9907398 ST5_L2, Transcriptome library
- GSM9907399 ST6_L1, Transcriptome library
- GSM9907400 ST7_C, Transcriptome library
- GSM9907401 ST7_R, Transcriptome library
- GSM9907402 ST7_T, Transcriptome library
- GSM9907403 ST8_C, Transcriptome library
- GSM9907404 ST8_T, Transcriptome library
- GSM9907405 ST9_C, Transcriptome library
- GSM9907406 ST9_T, Transcriptome library
- GSM9907407 ST10_T, Transcriptome library
- GSM9907408 ST11_C, Transcriptome library
- GSM9907409 ST11_T, Transcriptome library
- GSM9907410 ST12_C, Transcriptome library
- GSM9907411 ST12_T, Transcriptome library
- GSM9907412 ST13_C, Transcriptome library
- GSM9907413 ST13_T, Transcriptome library
- GSM9907414 ST14_C, Transcriptome library
- GSM9907415 ST14_T, Transcriptome library
- GSM9907416 ST15_C, Transcriptome library
- GSM9907417 ST15_T, Transcriptome library
- GSM9907418 ST16-C, Transcriptome library
- GSM9907419 ST16-R, Transcriptome library
- GSM9907420 ST16-T, Transcriptome library
- GSM9907421 ST17-CTX, Transcriptome library
- GSM9907422 ST17-T, Transcriptome library
- GSM9907423 ST18-T, Transcriptome library
- GSM9907424 ST20_CC, Transcriptome library
- GSM9907425 ST20_CT, Transcriptome library
- GSM9907426 ST20_RC, Transcriptome library
- GSM9907427 ST20_RT, Transcriptome library
- GSM9907428 ST21_C, Transcriptome library
- GSM9907429 ST21_OB, Transcriptome library
- GSM9907430 ST21_T, Transcriptome library
- GSM9907431 ST23_C, Transcriptome library
- GSM9907432 ST24_C, Transcriptome library
- GSM9907433 ST24_OB, Transcriptome library
- GSM9907434 ST24_R, Transcriptome library
- GSM9907435 ST24_T, Transcriptome library
- GSM9907436 ST25_C, Transcriptome library
+ 146 more — browse all 186 samples with per-sample file links →
- GSE223813 Spatiotemporal transcriptomic mapping of regenerative inflammation in skeletal muscle reveals a dynamic multilayered tissue architecture 10 samples shares spatiotemporal, architecture
- GSE266977 Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution 983 samples shares spatiotemporal
- GSE84371 Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons 924 samples shares newborn
- GSE277789 Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq-add] 830 samples shares spatiotemporal
- GSE235779 Compensatory growth and recovery of tissue cytoarchitecture after transient cartilage-specific cell death in foetal mouse limbs 68 samples shares architecture
- GSE284137 Tissue and cellular spatiotemporal dynamics in colon aging 395 samples shares spatiotemporal
- GSE233811 Spatiotemporal transcriptomic map of glial cell response in a mouse model of acute brain ischemia [bulk RNA-Seq] 48 samples shares spatiotemporal
- GSE296095 Benefits of Maternal choline supplementation on aged basal forebrain cholinergic neurons in a mouse model of Down syndrome and Alzheimer’s disease 44 samples shares forebrain
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.