Transcriptomic and Metabolomic Analyses Reveal Distinctive Metabolic Characteristics of Superficial and Deep Subcutaneous Adipose Tissues
RNA-seq (gene expression) · human · 12 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
- 12 samples: 6 × Superficial Sample vs 6 × Deep SampleGroups 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.
Read the full summary ↓
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 GSE216803_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 PRJNA895419 and SRA study SRP405092. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 2 replicated groups read from 12 sample titles; they account for 12 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.
- GSM6693175 Superficial Sample_11 Superficial Sample
- GSM6693176 Superficial Sample_12 Superficial Sample
- GSM6693177 Superficial Sample_13 Superficial Sample
- GSM6693178 Superficial Sample_14 Superficial Sample
- GSM6693179 Superficial Sample_15 Superficial Sample
- GSM6693180 Superficial Sample_16 Superficial Sample
- GSM6693181 Deep Sample_17 Deep Sample
- GSM6693182 Deep Sample_18 Deep Sample
- GSM6693183 Deep Sample_19 Deep Sample
- GSM6693184 Deep Sample_20 Deep Sample
- GSM6693185 Deep Sample_21 Deep Sample
- GSM6693186 Deep Sample_22 Deep Sample
- GSE329809 The Effect of Weight Loss on Metabolic Processes of the Abdominal Subcutaneous Adipose Tissue: An Exploratory Study using total RNA Next Generation Sequencing 18 samples shares subcutaneous, adipose
- GSE303983 Molecular responses in abdominal subcutaneous adipose tissue after a session of endurance exercise: effects of exercise intensity 90 samples shares subcutaneous, adipose
- GSE249089 Single-nucleus RNA-sequencing of human subcutaneous adipose tissue biopsies from 84 Finnish participants. 84 samples shares subcutaneous, adipose
- GSE245948 A dynamic subcutaneous adipose transcriptome of human insulin resistance identifies a molecular predisposition shared with visceral adipose tissue 76 samples shares subcutaneous, adipose
- GSE274778 Single-nucleus RNA sequencing of human subcutaneous adipose tissue biopsies from 68 Finnish participants. 68 samples shares subcutaneous, adipose
- GSE302701 Single-nucleus RNA sequencing of human subcutaneous adipose tissue biopsies from 59 Finnish participants. 59 samples shares subcutaneous, adipose
- GSE316698 Single-nucleus RNA sequencing of human subcutaneous adipose tissue biopsies from 49 Mexican participants 49 samples shares subcutaneous, adipose
- GSE306796 Human Subcutaneous ABD/GLU/Thi adipose tissue RNAseq - NYC sample 32 samples shares subcutaneous, adipose
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.