Transcriptomic profiling of human hepatocellular carcinoma biopsy samples using bulk RNA-seq
RNA-seq (gene expression) · human · 33 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Topic
- Hepatocellular carcinomaThis series is part of our curated briefing on it.
- Samples
- 33 samples: 33 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 GSE317207_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1398196 and SRA study SRP660684. 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 33 sample titles: 33 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.
- GSM9466994 Human hepatocellular carcinoma liver RNA-seq (HCC01)
- GSM9466995 Human hepatocellular carcinoma liver RNA-seq (HCC02)
- GSM9466996 Human hepatocellular carcinoma liver RNA-seq (HCC03)
- GSM9466997 Human hepatocellular carcinoma liver RNA-seq (HCC04)
- GSM9466998 Human hepatocellular carcinoma liver RNA-seq (HCC05)
- GSM9466999 Human hepatocellular carcinoma liver RNA-seq (HCC06)
- GSM9467000 Human hepatocellular carcinoma liver RNA-seq (HCC07)
- GSM9467001 Human hepatocellular carcinoma liver RNA-seq (HCC08)
- GSM9467002 Human hepatocellular carcinoma liver RNA-seq (HCC09)
- GSM9467003 Human hepatocellular carcinoma liver RNA-seq (HCC10)
- GSM9467004 Human hepatocellular carcinoma liver RNA-seq (HCC11)
- GSM9467005 Human hepatocellular carcinoma liver RNA-seq (HCC12)
- GSM9467006 Human hepatocellular carcinoma liver RNA-seq (HCC13)
- GSM9467007 Human hepatocellular carcinoma liver RNA-seq (HCC14)
- GSM9467008 Human hepatocellular carcinoma liver RNA-seq (HCC15)
- GSM9467009 Human hepatocellular carcinoma liver RNA-seq (HCC16)
- GSM9467010 Human hepatocellular carcinoma liver RNA-seq (HCC17)
- GSM9467011 Human hepatocellular carcinoma liver RNA-seq (HCC18)
- GSM9467012 Human hepatocellular carcinoma liver RNA-seq (HCC19)
- GSM9467013 Human hepatocellular carcinoma liver RNA-seq (HCC20)
- GSM9467014 Human hepatocellular carcinoma liver RNA-seq (HCC21)
- GSM9467015 Human hepatocellular carcinoma liver RNA-seq (HCC22)
- GSM9467016 Human hepatocellular carcinoma liver RNA-seq (HCC23)
- GSM9467017 Human hepatocellular carcinoma liver RNA-seq (HCC24)
- GSM9467018 Human hepatocellular carcinoma liver RNA-seq (HCC25)
- GSM9467019 Human hepatocellular carcinoma liver RNA-seq (HCC26)
- GSM9467020 Human hepatocellular carcinoma liver RNA-seq (HCC27)
- GSM9467021 Human hepatocellular carcinoma liver RNA-seq (HCC28)
- GSM9467022 Human hepatocellular carcinoma liver RNA-seq (HCC29)
- GSM9467023 Human hepatocellular carcinoma liver RNA-seq (HCC30)
- GSM9467024 Human hepatocellular carcinoma liver RNA-seq (HCC31)
- GSM9467025 Human hepatocellular carcinoma liver RNA-seq (HCC32)
- GSM9467026 Human hepatocellular carcinoma liver RNA-seq (HCC33)
- 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
- GSE14520 Gene expression data of human hepatocellular carcinoma (HCC) 488 samples same disease briefing · shares hepatocellular
- GSE10143 Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma 387 samples same disease briefing · shares hepatocellular
- GSE107170 Molecular Signature of Hepatitis D Virus-Associated Hepatocellular Carcinoma 307 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
- GSE114564 Identification of novel serum biomarkers in early-stage HCC patients. 118 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.