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Identification of novel serum biomarkers in early-stage HCC patients.

GSE114564 Homo sapiens (human) RNA-seq (gene expression) 118 samples Submitted 2020/12/31 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 118 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
118 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)
Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide, and is the one of the few cancers in which a continued increase in incidence has been observed over several years. HCC associated with chronic liver disease evolves from precancerous lesion and early HCC to overt cancer, and identifying key molecules contributing to early stage HCC is an urgent need.
Read the full summary ↓
α-Fetoprotein (AFP) is the best serum biomarker for diagnosis of HCC, but sensitivity is low, particularly in detection of early-stage HCC. Therefore, novel and reliable diagnostic biomarkers to complement AFP are needed to improve HCC diagnosis. We aim to determine transcriptome-based molecular signature of multistep hepatocarcinogenesis, and to identify novel serum biomarkers to diagnose early stage HCC patient.
This dataset
Open GSE114564 in finder → Find more human RNA-seq datasets → Hepatocellular carcinoma 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 GSE114564_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: 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 PRJNA471801 and SRA study SRP148066. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 35205612) ↗
Samples in this study

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+ 118 more — browse all 118 samples with per-sample file links →

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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.