Single-cell RNA sequencing of tumor tissues from 12 colorectal cancer (CRC) patients.
Single-cell RNA-seq · human · 12 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
- 12 samples
- 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
- Agonist signaling drives neutrophil subpopulations to promote/inhibit colorectal cancer liver metastasisNature communications · 2025
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 GSE302903_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 PRJNA1292798 and SRA study SRP601571. Searching any of these in the dataset finder brings you back here.
The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Sample titles run T1 … T12 and carry no group information.
- GSM9113377 T1
- GSM9113378 T2
- GSM9113379 T3
- GSM9113380 T4
- GSM9113381 T5
- GSM9113382 T6
- GSM9113383 T7
- GSM9113384 T8
- GSM9113385 T9
- GSM9113386 T10
- GSM9113387 T11
- GSM9113388 T12
- GSE294559 Single-cell multi-omics characterize colorectal tumors, adjacent healthy tissue and matched organoids identifying CRC-unique features 72 samples shares crc, single-cell, colorectal
- GSE315534 Single-cell RNA sequencing of primary colorectal cancer, matched adjacent normal tissues, and paired liver metastases 15 samples shares single-cell, colorectal
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares single-cell, colorectal
- GSE292858 RNA-Seq analysis of tumor and matched normal samples from colorectal cancer patients. 73 samples shares colorectal
- GSE328275 Single-cell RNA sequencing of CD45+ immune cells across primary tumor, sentinel tumor-draining lymph node, and axillary lymph node in treatment-naive triple-negative breast cancer 28 samples shares single-cell
- GSE313035 METIMMOX: Colorectal Cancer METastasis - Shaping Anti-tumor IMMunity by OXaliplatin 67 samples shares colorectal
- GSE205472 A Single-Cell Atlas of HR+ Breast Cancer Reveals the Shifting of the Tumor Microenvironment in Response to Neoadjuvant Chemotherapy 13 samples shares single-cell
- GSE277524 Single-cell dissection of multifocal bladder cancer reveals malignant and immune cells variation between primary and recurrence tumor lesions 10 samples shares 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.