snRNA-Seq from Younger and Older human abdominal subcutaneous white adipose tissue
Single-nucleus RNA-seq · human · 10 samples
- What it is
- Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 10 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.
- Paper
- Aging human abdominal subcutaneous white adipose tissue at single cell resolutionAging cell · 2024
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 GSE235529_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA986227 and SRA study SRP445265. 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 10 sample titles: 10 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.
- GSM7504775 snRNASeq_BA01_and_BA08
- GSM7504776 snRNASeq_BA07_and_BA09
- GSM7504777 snRNASeq_BA10_and_BA15
- GSM7504778 snRNASeq_BA14_and_BA16
- GSM7504779 snRNASeq_BA17_and_BA18
- GSM7504780 snRNASeq_BA19_and_BA24
- GSM7504781 snRNASeq_BA20_and_BA22
- GSM7504782 snRNASeq_BA23_and_BA06
- GSM7504783 snRNASeq_BA26_and_BA27
- GSM7504784 snRNASeq_BA30_and_BA31
- GSE303983 Molecular responses in abdominal subcutaneous adipose tissue after a session of endurance exercise: effects of exercise intensity 90 samples shares subcutaneous, abdominal, adipose
- GSE287627 Human Subcutaneous abdominal adipose tissue RNAseq - NYC sample 19 samples shares subcutaneous, abdominal, adipose
- 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, abdominal, adipose
- GSE306825 Heterogeneity in populations from subcutaneous abdominal and thigh adipose tissues of women 14 samples shares subcutaneous, abdominal, adipose
- GSE297258 Single-cell DNA methylome and 3D genome atlas of human subcutaneous adipose tissue [snRNA-Seq] 11 samples shares subcutaneous, snrna-seq, adipose
- GSE296628 Brown remodeling of white adipose tissue protects against abdominal aortic aneurysm via a novel batokine FSTL1 6 samples shares abdominal, adipose, white
- GSE322696 snRNA-Seq from abdominal and gluteofemoral human adipose tissue 5 samples shares snrna-seq, abdominal, adipose
- GSE310542 A single-nucleus dataset sampling subcutaneous white adipose from living donors to study familial partial lipodystrophy 2 30 samples shares subcutaneous, adipose, white
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.