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Beige Fat, Energy, and the Natriuretic Peptide System

GSE253305 Homo sapiens (human) RNA-seq (gene expression) 71 samples Submitted 2024/10/24 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 71 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
71 samples: 51 × KB vs 20 × RTGroups 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.
Paper
The subcutaneous adipose transcriptome identifies a molecular signature of insulin resistance shared with visceral adiposeObesity (Silver Spring, Md.) · 2024
Summary (written by the submitters)
The purpose of this study is to learn how types of fat profiles differ between lean and obese individuals, and how they differ between racial groups. We are also interested in learning about the relationship of fat profiles with natriuretic peptide hormones, which are hormones produced by the heart. We will measure this by collecting tissue, blood and urine samples, energy expenditure measurements using the metabolic cart, and a DXA to assess the amount of bone, fat and muscle in the body from a single study visit.
Published in
The subcutaneous adipose transcriptome identifies a molecular signature of insulin resistance shared with visceral adipose
Mashayekhi M, Sheng Q, Bailin SS et al. · Obesity (Silver Spring, Md.) 2024 · PMID 38967296 · doi:10.1002/oby.24064
This dataset
Open GSE253305 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 GSE253305_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 PRJNA1065008 and SRA study SRP483842. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38967296) ↗
Study design
51 × KB vs 20 × RT

Supports a between-group comparison across 71 samples.

How we read this: 2 replicated groups read from 71 sample titles; they account for 71 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

+ 31 more — browse all 71 samples with per-sample file links →

Datasets on a similar topic

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.