Deciphering hypoxia related glioblastoma-associated macrophages and predicting prognostic markers by single-cell, spatially-resolved transcriptomics and experimental analysis
Single-cell RNA-seq · human · 17 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)
- Topic
- GlioblastomaThis series is part of our curated briefing on it.
- Samples
- 17 samples: 12 × ID_S vs 3 × ID vs 2 × SGroups 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.
Read the full summary ↓
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 GSE305549_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 PRJNA1306491 and SRA study SRP609128. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 17 samples.
How we read this: 3 replicated groups read from 17 sample titles; they account for 17 of them. 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.
- GSM9179253 ID_S013 ID_S
- GSM9179254 ID_S038 ID_S
- GSM9179255 ID_S009 ID_S
- GSM9179256 ID_S026 ID_S
- GSM9179257 ID_S005 ID_S
- GSM9179258 ID_S025 ID_S
- GSM9179259 ID_S006 ID_S
- GSM9179260 ID_S036 ID_S
- GSM9179261 ID_S041 ID_S
- GSM9179262 ID_S039 ID_S
- GSM9179263 ID_S004 ID_S
- GSM9179264 ID_S018 ID_S
- GSM9179265 ID_008 ID
- GSM9179266 ID_017 ID
- GSM9179267 ID_020 ID
- GSM9552992 S250729 S
- GSM9552993 S250801 S
- GSE13041 Gene expression analysis of glioblastomas identifies the major molecular basis for the prognostic benefit of younger age 267 samples same disease briefing · shares prognostic
- GSE231555 Splicing and gene expression changes in cell lines treated with splicing switching oligonucleotide targeting TRA2B 46 samples same disease briefing
- GSE112648 SOXC factors as suppressors modulate Rho activity to promote neuronal reprogramming of human glioblastoma cells 18 samples same disease briefing
- GSE131928 single cell RNA-seq analysis of adult and paediatric IDH-wildtype Glioblastomas 2 samples same disease briefing
- GSE107560 Ivy Glioblastoma Atlas Project 305 samples same disease briefing
- GSE10878 Integrative Genome-wide Analysis of Glioblastoma. 60 samples same disease briefing
- GSE112650 SOX4/11 Enhances NGN2 Reprogramming Glioblastoma Cells into Neuron Cells by Modulating RhoA and CDC42/RAC1 Pathway Activity 30 samples same disease briefing
- GSE112645 SOXC factors as suppressors modulate Rho activity to promote neuronal reprogramming of human glioblastoma cells 12 samples same disease briefing
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.