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The proteomic and transcriptomic profiles of gastric mucosa from health volunteers

GSE250499 Homo sapiens (human) RNA-seq (gene expression) 68 samples Submitted 2024/04/01 Platform GPL23227
At a glance

RNA-seq (gene expression) · human · 68 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)
Samples
68 samples: 19 conditions, mostly in duplicateGroups 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.
Summary (written by the submitters)
As the important layer of the stomach wall, gastric mucosa is related to many functions of digestion. According to the anatomical location, the human stomach is divided into seven regions. In order to get an entire profiling of the 7 regions at proteomic and transcriptomic levels, we collected 7 biopsies from each health volunteer, 49 total were used for integrative analysis, and measured the regional-specific gene products to define the reference intervals of gene expression for outliers screening and prognostic gene detection.
Read the full summary ↓
Collectively, we presented profiling of normal gastric mucosa at different levels and defined reference ranges of gene expression to study the specific characteristics of abnormal and cancer samples, providing a better understanding of stomach physiological function in studies of gastric disease mechanism.
This dataset
Open GSE250499 in finder → Find more human RNA-seq datasets →
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 GSE250499_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 PRJNA1054173 and SRA study SRP478701. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
19 conditions, mostly in duplicate
gastric mucosa, pylorus A7 ×2 gastric mucosa, fundus B2 ×2 gastric mucosa, lesser curvature B3 ×2 gastric mucosa, greater curvature B4 ×2 gastric mucosa, angular incisure B5 ×2 gastric mucosa, greater curvature C4 ×2 gastric mucosa, antrum C6 ×2 gastric mucosa, pylorus C7 ×2 +41 more

Supports a between-group comparison across 38 samples.

How we read this: 19 replicated groups read from 68 sample titles; they account for 38 of them. 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.

Samples in this study

+ 28 more — browse all 68 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.