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Whole-Transcriptome RNA-Seq of Kidney Tissue from Patients in the Alport Spectrum

GSE318857 Homo sapiens (human) RNA-seq (gene expression) 93 samples Submitted 2026/08/26 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 93 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
93 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.
Summary (written by the submitters)
Alport syndrome encompasses a spectrum of glomerular basement membrane disorders associated with pathogenic variants in COL4A3, COL4A4, and COL4A5. In this study, bulk whole-transcriptome RNA sequencing was performed on kidney biopsy tissue from 93 samples exhibiting GBM alterations consistent with the Alport spectrum. The dataset includes transcript abundance, alternative splicing, and exon usage information for collagen IV–related and other GBM-associated genes.
Read the full summary ↓
Publicly available normal kidney transcriptome data from the GTEx project were used as an external reference for selected downstream analyses but are not included in this GEO submission. This dataset provides a resource for investigating transcriptomic variation and splicing complexity in kidney tissue from individuals with Alport spectrum disorders and related nephropathies.
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE318857_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA1420726 and SRA study SRP675746. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 93 more — browse all 93 samples with per-sample file links →

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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.