Single-cell RNA sequencing of murine kidneys for ischemia-reperfusion induced renal injury and fibrosis
Single-cell RNA-seq · mouse · 10 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 10 samples: 3 × IR D vs 2 × IR HGroups 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.
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 GSE274819_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 PRJNA1148121 and SRA study SRP526407. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 5 samples.
How we read this: 2 replicated groups read from 10 sample titles; they account for 5 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.
- GSM8458383 ShamA
- GSM8458384 ShamB
- GSM8458385 IR H4 IR H
- GSM8458386 IR H12 IR H
- GSM8458387 IR D1 IR D
- GSM8458388 IR D5A
- GSM8458389 IR D5B
- GSM8458390 IR D5C
- GSM8458391 IR D14 IR D
- GSM8458392 IR D28 IR D
- GSE264278 TIme-cource single-cell RNA-seq analysis of bleomycin and LPS-induced lung injury and fibrosis 18 samples shares single-cell, fibrosis, induced, injury
- GSE309471 Single-cell RNA sequencing of lung cells from bleomycin-induced and doxycycline-inducible TGF-β transgenic mouse models of pulmonary fibrosis 46 samples shares single-cell, fibrosis, induced
- GSE276682 Single-cell transcriptome analysis revealed cellular reprogramming following Tetramethylpyrazine treatment in LPS-induced acute lung injury 12 samples shares single-cell, induced, injury
- GSE192687 Single-cell RNAseq analysis of renal endothelial cells in murine diabetic nephropathy 5464 samples shares single-cell, renal
- GSE307265 Experimentally induced myocardial infarction in mice - RNA Sequencing of kidneys 24 samples shares kidneys, induced
- GSE239287 Single-cell transcriptome sequencing of macrophages in acute kidney injury(AKI) to chronic kidney dieases(CKD) 17 samples shares single-cell, injury
- GSE329706 Single-cell RNA sequencing of the mouse hippocampus after spared nerve injury (SNI) modeling 11 samples shares single-cell, injury
- GSE280003 Gpnmb and Spp1 mark a conserved macrophage injury response masking fibrosis-specific programming in the lung 81 samples shares fibrosis, injury
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.