miRNA and mRNA Signatures in Human Acute Kidney Injury Tissue [mRNA, minimal change disease]
RNA-seq (gene expression) · human · 12 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 12 samples
- 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
- Inflammation primes the murine kidney for recovery by activating AZIN1 adenosine-to-inosine editingThe Journal of clinical investigation · 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 GSE246204_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1032050 and SRA study SRP468363. Searching any of these in the dataset finder brings you back here.
The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Sample titles run M1 … M12 and carry no group information.
- GSM7864794 M1
- GSM7864795 M2
- GSM7864796 M3
- GSM7864797 M4
- GSM7864798 M5
- GSM7864799 M6
- GSM7864800 M7
- GSM7864801 M8
- GSM7864802 M9
- GSM7864803 M10
- GSM7864804 M11
- GSM7864805 M12
- GSE246206 miRNA and mRNA Signatures in Human Acute Kidney Injury Tissue 112 samples shares signatures, kidney, injury, mirna, acute, mrna
- GSE178411 Whole-transcriptome analysis illustrates evolving transcriptional human response to injury in acute wounds and scars 108 samples shares injury, acute
- GSE316742 SGLT2 inhibition reverses metabolic and inflammatory kidney signatures in youth with type 1 diabetes 27 samples shares signatures, kidney
- GSE315877 Metabolic surgery mitigates early kidney injury in obese youth with diabetes by suppressing mTORC1/JAK–STAT signaling 16 samples shares kidney, injury
- GSE249812 Dynamic molecular signatures of acute myocardial infarction based on transcriptomics 15 samples shares signatures, acute
- GSE277476 Altered bone marrow myelopoiesis contributes to kidney injury [scRNA-seq] 11 samples shares kidney, injury
- GSE286042 Transcriptomic and Proteomic Signatures Following AS03-adjuvanted Influenza A/H7N9 Vaccine 1232 samples shares signatures
- GSE280113 Progenitor effects and unique transcriptomic signatures linked to differentiation phenotype in clonally expanded antigen-specific CD8 T memory stem cells (TSCM) 509 samples shares signatures
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.