scRNAseq profile of hepatocellular carcinoma (HCC) tumors and adjacent tissues with or without hepatitis-B virus (HBV) infection
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)
- Topic
- Hepatocellular carcinomaThis series is part of our curated briefing on it.
- Samples
- 12 samples: 12 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.
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 GSE282701_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 PRJNA1189822 and SRA study SRP547168. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 6 samples read as cases, 6 as controls.
How we read this: Read from 12 sample titles: 12 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.
- GSM8649020 P15,tumor,HBV-ne
- GSM8649021 P15,adjacent,HBV-ne
- GSM8649022 P14,tumor,HBV-ne
- GSM8649023 P14,adjacent,HBV-ne
- GSM8649024 P13,tumor,HBV-po
- GSM8649025 P13,adjacent,HBV-po
- GSM8649026 P12,tumor,HBV-po
- GSM8649027 P12,adjacent,HBV-po
- GSM8649028 P11,tumor,HBV-ne
- GSM8649029 P11,adjacent,HBV-ne
- GSM8649030 P10,tumor,HBV-po
- GSM8649031 P10,adjacent,HBV-po
- GSE14520 Gene expression data of human hepatocellular carcinoma (HCC) 488 samples same disease briefing · shares hcc, hepatocellular
- GSE107170 Molecular Signature of Hepatitis D Virus-Associated Hepatocellular Carcinoma 307 samples same disease briefing · shares hepatocellular, virus
- GSE114564 Identification of novel serum biomarkers in early-stage HCC patients. 118 samples same disease briefing · shares hcc
- GSE105130 Comprehensive analysis of Transcriptome Profiles in Hepatocellular Carcinoma patients 52 samples same disease briefing · shares hepatocellular
- GSE140228 Landscape and Dynamics of Single Immune Cells in Hepatocellular Carcinoma 41 samples same disease briefing · shares hepatocellular
- GSE10143 Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma 387 samples same disease briefing · shares hepatocellular
- GSE109211 Molecular predictors of prevention of recurrence in hepatocellular carcinoma with sorafenib as adjuvant treatment in the phase 3 STORM trial 140 samples same disease briefing · shares hepatocellular
- GSE10186 Integrative Transcriptome Analysis Reveals Common Molecular Subtypes of Human Hepatocellular Carcinoma 118 samples same disease briefing · shares hepatocellular
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.