GEO series

Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

GSE81861 Homo sapiens (human) Single-cell RNA-seq 1220 samples Submitted 2017/03/20 Platform GPL11154

At a glance

Single-cell RNA-seq · human · 1220 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: Colorectal cancerThis series is part of our curated briefing on it.
Samples: 1220 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.

Summary (written by the submitters)

Intratumoralmheterogeneity is a major obstacle to cancer treatment and a significant confounding factor in bulk-tumor profiling. We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA–seq from 11 primary colorectal tumors and matched normal mucosa. To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy.

Read the full summary ↓

Using RCA, we identified two distinct subtypes of cancer-associated fibroblasts (CAFs). Additionally, epithelial–mesenchymal transition (EMT)-related genes were found to be upregulated only in the CAF subpopulation of tumor samples. Notably, colorectal tumors previously assigned to a single subtype on the basis of bulk transcriptomics could be divided into subgroups with divergent survival probability by using single-cell signatures, thus underscoring the prognostic value of our approach. Overall, our results demonstrate that unbiased single-cell RNA–seq profiling of tumor and matched normal samples provides a unique opportunity to characterize aberrant cell states within a tumor.

This dataset

Open GSE81861 in finder → Find more human RNA-seq datasets → Colorectal cancer landscape →

Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE81861_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA323703. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 28319088) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 1220 more — browse all 1220 samples with per-sample file links →

More Colorectal cancer datasets

GSE250000 Bulk RNA-sequencing of transduced colorectal cancer cell line HCT-116 and breast cancer cell line MCF-7 overexpressing full-lenght p53β or p53β-stop-lost. 4 samples same disease briefing · shares colorectal
GSE12032 Inherent gene signature of stage II and III colorectal cancer leads in individual recurrence 198 samples same disease briefing · shares colorectal
GSE109308 Single-cell transcriptomic survey of adenomatous polyposis patients with germline APC mutations 97 samples same disease briefing · shares single-cell
GSE110009 Single cell transcriptome landscape of primary and metastatic tumor in colon cancer 76 samples same disease briefing
GSE124480 Gene expression of human colon cancer HCT116 cells 5 samples same disease briefing
GSE243013 A single-cell atlas of immune heterogeneity in anti-PD1-treated non-small cell lung cancer 243 samples shares heterogeneity, 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, colorectal
GSE278688 Integrated Single-Cell and Spatial Transcriptomics Uncover Distinct Cellular Subtypes Involved in Neural Invasion in PDAC [scRNA-Seq] 29 samples shares single-cell, cellular

Search all human RNA-seq datasets in GEO →

Share this dataset

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.