Single nucleus RNA-sequencing atlas of pediatric solid tumors
Single-nucleus RNA-seq · human · 182 samples
- What it is
- Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 182 samples: 160 distinct titles, 20 of them repeatedGroups 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
- Integrative Single-cell and Spatial Transcriptomic Analysis of Osteosarcoma Reveals Conserved and Distinct Ecosystems Across Sites and SpeciesbioRxiv : the preprint server for biology · 2026
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 GSE293805_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 PRJNA1246412 and SRA study SRP576497. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 182 sample titles: 160 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.
- GSM8890296 SJACT030686_D1
- GSM8890297 SJACT030812_D1
- GSM8890298 SJACT030812_D2
- GSM8890299 SJCCS030167_D3
- GSM8890300 SJCCS030604_R1
- GSM8890301 SJDSRCT030722_D1
- GSM8890302 SJDSRCT046151_D1
- GSM8890303 SJDSRCT049192_D1
- GSM8890304 SJDSRCT049192_R1
- GSM8890305 SJUESL030381_D1
- GSM8890306 SJSTS046147_R1
- GSM8890307 SJEWS001321_D2
- GSM8890308 SJEWS049193_D1
- GSM8890309 SJEWS049193_D2
- GSM8890310 SJEWS063826_D1
- GSM8890311 SJEWS063829_D1
- GSM8890312 SJEWS063834_A1
- GSM8890313 SJEWS063834_A2
- GSM8890314 SJGCT030372_D1
- GSM8890315 SJGIST030657_D1
- GSM8890316 SJHB030622_D1
- GSM8890317 SJHGS012410_D1
- GSM8890318 SJHGS012411_D1
- GSM8890319 SJHGS015726_D1
- GSM8890320 SJHGS015726_D2
- GSM8890321 SJIFS030375_R1
- GSM8890322 SJMEL030083_D1
- GSM8890323 SJMEL030083_D2
- GSM8890324 SJMEL063827_D1
- GSM8890325 SJMRT015723_D1
- GSM8890326 SJSTS030873_D1
- GSM8890327 SJMRT063832_D1
- GSM8890328 SJMRT031055_D1
- GSM8890329 SJNBL047443_R1
- GSM8890330 SJNBL047443_R1_repB
- GSM8890331 SJOS001105_M1
- GSM8890332 SJOS001107_M2
- GSM8890333 SJOS001108_M1
- GSM8890334 SJOS001112_M2
- GSM8890335 SJOS001116_M2
+ 142 more — browse all 182 samples with per-sample file links →
- GSE319124 Next-GenerationPediatric Cancer Models: Patient-Matched Orthotopic Xenografts, 3D Organoids, 2D Cultures, and Cell Lines for Identification of Therapeutic Vulnerabilities in Pediatric Solid Tumors [scRNAseq] 59 samples shares pediatric, solid
- GSE184487 RNA-sequencing of PBMC cultured with PolyI:C or LPS, from a pediatric cohort who received OM85 or placebo. 193 samples shares rna-sequencing, pediatric
- GSE306609 Sensitive CAR T cells redefine targetable CD70 expression in solid tumors [RNA-seq RCC] 55 samples shares solid
- GSE330227 In vivo genome-wide CRISPR screens in human T cells to enhance T cell therapy for solid tumors 30 samples shares solid
- GSE313197 Tumor Antigen–Independent Targeting of Solid Tumors by Armored 1 Macrophage-Directed anti-TREM2-CAR T Cells [human scRNA-seq] 23 samples shares solid
- GSE341101 scRNA-sequencing of gastric tissues derived from eight inflamed-type and eight desert-type tumors 16 samples shares rna-sequencing
- GSE308103 Single-nucleus RNA-sequencing (snRNA-seq) analysis of normal lung tissues, precursor lung lesions and invasive lung adenocarcinomas 75 samples shares rna-sequencing
- GSE264680 Leveraging Single-Cell Sequencing to Classify and Characterize Tumor Subgroups in Bulk RNA-Sequencing Data 167 samples shares rna-sequencing
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.