Urinary Clusterin as a Biomarker of Human Kidney Disease Progression and Response to the Endothelin Receptor Antagonist Atrasentan: An Exploratory Analysis from the SONAR Trail
Single-cell RNA-seq · mouse · 17 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Mus musculus (mouse)
- Samples
- 17 samples: 17 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
- Urinary clusterin as a biomarker of human kidney disease progression and response to the endothelin receptor antagonist atrasentan: An exploratory analysis from the SONAR trialNature communications · 2026
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 GSE307122_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 PRJNA1314634 and SRA study SRP616829. 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 17 sample titles: 17 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.
- GSM9216873 Sample_92799_BTBR ob_Atra
- GSM9216874 Sample_92809_ob/ob-d30_Saline
- GSM9216875 Sample_92807_ob/ob-d30_Saline
- GSM9216876 Sample_92796_BTBR ob_Atra
- GSM9216877 Sample_92798_BTBR ob_Atra
- GSM9216878 Sample_92805_ob/ob-d30_Saline
- GSM9216879 Sample_92810_WT-d30_
- GSM9216880 Sample_92812_WT-d30_
- GSM9216881 Sample_92814_WT-d30_
- GSM9216882 Sample_92800_BTBR ob_Atra
- GSM9216883 Sample_92795_BTBR ob_Atra
- GSM9216884 Sample_92813_WT-d30_
- GSM9216885 Sample_92811_WT-d30_
- GSM9216886 Sample_92801_BTBR ob_Atra
- GSM9216887 Sample_92808_ob/ob-d30_Saline
- GSM9216888 Sample_92806_ob/ob-d30_Saline
- GSM9216889 Sample_92797_BTBR ob_Atra
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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.