Targeting Set7 in an experimental model of diabetic nephropathy
Single-cell RNA-seq · mouse · 28 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
- 28 samples: 9 conditions, mostly with about 4 replicates eachGroups 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
- Set7 Methyltransferase and Phenotypic Switch in Diabetic Glomerular Endothelial CellsJournal of the American Society of Nephrology : JASN · 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 GSE158626_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 PRJNA666001 and SRA study SRP285544. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 28 samples.
How we read this: 9 replicated groups read from 28 sample titles; they account for 28 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.
- GSM4804554 Setd7 KO Kidney - Control 561 Setd7 KO Kidney - Contr…
- GSM4804555 Setd7 KO Kidney - Control 562 Setd7 KO Kidney - Contr…
- GSM4804556 Setd7 KO Kidney - Diabetic 562 Setd7 KO Kidney - Diabe…
- GSM4804557 Setd7 KO Kidney - Diabetic 567 Setd7 KO Kidney - Diabe…
- GSM4804558 Setd7 WT Kidney - Control 370 Setd7 WT Kidney - Contr…
- GSM4804559 Setd7 WT Kidney - Control 372 Setd7 WT Kidney - Contr…
- GSM4804560 Setd7 WT Kidney - Diabetic 373 Setd7 WT Kidney - Diabe…
- GSM4804561 Setd7 WT Kidney - Diabetic 374 Setd7 WT Kidney - Diabe…
- GSM8215209 GEC_NG_1 GEC_NG
- GSM8215210 GEC_NG_2 GEC_NG
- GSM8215211 GEC_NG_3 GEC_NG
- GSM8215212 GEC_NG_4 GEC_NG
- GSM8215213 GEC_PFI_1 GEC_PFI
- GSM8215214 GEC_PFI_2 GEC_PFI
- GSM8215215 GEC_PFI_3 GEC_PFI
- GSM8215216 GEC_PFI_4 GEC_PFI
- GSM8215217 GEC_TGF_1 GEC_TGF
- GSM8215218 GEC_TGF_2 GEC_TGF
- GSM8215219 GEC_TGF_3 GEC_TGF
- GSM8215220 GEC_TGF_4 GEC_TGF
- GSM8215221 KD_TGF_1 KD_TGF
- GSM8215222 KD_TGF_2 KD_TGF
- GSM8215223 KD_TGF_3 KD_TGF
- GSM8215224 KD_TGF_4 KD_TGF
- GSM8215225 NT_TGF_1 NT_TGF
- GSM8215226 NT_TGF_2 NT_TGF
- GSM8215227 NT_TGF_3 NT_TGF
- GSM8215228 NT_TGF_4 NT_TGF
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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.