← BioTransfer GEO Dataset Finder
GEO series

Single-Cell multi-omics reveals disrupted gene regulatory landscape and cell differentiation by Wilms tumor-associated ENL mutation in the developing kidney (scRNA-Seq)

GSE243870 Mus musculus (mouse) Single-cell RNA-seq 3 samples Submitted 2024/05/27 Platform GPL30172
At a glance

Single-cell RNA-seq · mouse · 3 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
3 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
Single-cell multiomics reveals ENL mutation perturbs kidney developmental trajectory by rewiring gene regulatory landscapeNature communications · 2024
Summary (written by the submitters)
ENL is an epigenetic acetylation reader and represents the most frequently mutated epigenetic regulator in Wilms tumor. In this study, we established an in vivo mouse model with the ENL hotspot mutation Enl-T1. We performed single-cell RNA sequencing (scRNA-seq) analysis for the Enl-WT and T1 embryonic kidney to study the transcriptional mechanism underlying the kidney developing defeat induced by the Enl mutation.
Published in
Single-cell multiomics reveals ENL mutation perturbs kidney developmental trajectory by rewiring gene regulatory landscape
Song L, Li Q, Xia L et al. · Nature communications 2024 · PMID 39009564 · doi:10.1038/s41467-024-50171-w
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 GSE243870_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: 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 PRJNA1020193 and SRA study SRP462754. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 3 more — browse all 3 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.