Metabolic surgery mitigates early kidney injury in obese youth with diabetes by suppressing mTORC1/JAK–STAT signaling
Single-cell RNA-seq · human · 16 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
- Homo sapiens (human)
- Samples
- 16 samples: 6 × Healthy control vs 5 × Biol rep 1 Patient vs 5 × Biol rep 2 PatientGroups 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
- Metabolic surgery mitigates early kidney injury in obese youth with diabetes by suppressing mTORC1/JAK/STAT signalingThe Journal of clinical investigation · 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 GSE315877_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 PRJNA1399477. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 10 samples read as cases, 6 as controls.
How we read this: 3 replicated groups read from 16 sample titles; they account for 16 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.
- GSM9438972 Biol rep 1 Patient 1 Biol rep 1 Patient
- GSM9438973 Biol rep 2 Patient 1 Biol rep 2 Patient
- GSM9438974 Biol rep 1 Patient 2 Biol rep 1 Patient
- GSM9438975 Biol rep 2 Patient 2 Biol rep 2 Patient
- GSM9438976 Biol rep 1 Patient 3 Biol rep 1 Patient
- GSM9438977 Biol rep 2 Patient 3 Biol rep 2 Patient
- GSM9438978 Biol rep 1 Patient 4 Biol rep 1 Patient
- GSM9438979 Biol rep 2 Patient 4 Biol rep 2 Patient
- GSM9438980 Biol rep 1 Patient 5 Biol rep 1 Patient
- GSM9438981 Biol rep 2 Patient 5 Biol rep 2 Patient
- GSM9438982 Healthy control 1 Healthy control
- GSM9438983 Healthy control 2 Healthy control
- GSM9438984 Healthy control 3 Healthy control
- GSM9438985 Healthy control 4 Healthy control
- GSM9438986 Healthy control 5 Healthy control
- GSM9438987 Healthy control 6 Healthy control
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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.