Single-cell multiomics profiling reveals heterogeneous transcriptional programs and microenvironment in Desmoplastic Small Round Cell Tumors [scRNA-Seq]
Single-cell RNA-seq · human · 11 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 11 samples: 11 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 multiomics profiling reveals heterogeneous transcriptional programs and microenvironment in DSRCTsCell reports. Medicine · 2024
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 GSE263521_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 PRJNA1097964. 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 11 sample titles: 11 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.
- GSM8193966 GR2 patient, site 1, scRNAseq
- GSM8193967 GR2 patient, site 2, scRNAseq
- GSM8193968 GR2 patient, site 3, scRNAseq
- GSM8193969 GR2 patient, site 4, scRNAseq
- GSM8193970 GR4 patient, scRNAseq
- GSM8193971 GR4 patient, post chemotherapy, scRNAseq
- GSM8193972 IC patient, site 1, scRNAseq
- GSM8193973 IC patient, site 2, scRNAseq
- GSM8193974 IC patient, site 3, scRNAseq
- GSM8193975 GR7 patient, site 1, scRNAseq
- GSM8193976 GR7 patient, site 2, scRNAseq
- GSE297041 Chemoradiation Reprograms Tumor Cells and Immune Microenvironment In Cervical Cancer [scRNA-seq] 18 samples shares microenvironment, scrna-seq, programs
- GSE309595 Longitudinal Analysis of Multiple Myeloma: Therapeutic Response and Immune Microenvironment Dynamics in the Context of Tumor Heterogeneity [scRNA-seq] 270 samples shares microenvironment, scrna-seq
- GSE243013 A single-cell atlas of immune heterogeneity in anti-PD1-treated non-small cell lung cancer 243 samples shares single-cell, small
- GSE263733 Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications 218 samples shares microenvironment, single-cell
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares single-cell, scrna-seq
- GSE198315 Multiregional single-cell profiling reveals extensive field cancerization and an immunosuppressive microenvironment in oral squamous cell carcinoma 36 samples shares microenvironment, single-cell
- GSE337246 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [scRNA-Seq organoids] 35 samples shares single-cell, scrna-seq
- GSE278688 Integrated Single-Cell and Spatial Transcriptomics Uncover Distinct Cellular Subtypes Involved in Neural Invasion in PDAC [scRNA-Seq] 29 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.