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Targeting Immune-Fibroblast Crosstalk in Myocardial Infarction and Cardiac Fibrosis I

GSE217494 Homo sapiens (human) Single-cell RNA-seq 44 samples Submitted 2024/07/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 44 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
Homo sapiens (human)
Samples
44 samples: 22 × GEX_sample vs 22 × Ab_sampleGroups 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
Targeting immune-fibroblast cell communication in heart failureNature · 2024
Summary (written by the submitters)
To define the cellular landscape of human myocardial infarction and heart failure, we performed Cellular Indexing of Transcriptomes and Epitomes by sequencing (CITE-seq) in 22 explanted human hearts from healthy donors, acute myocardial infarction (MI),and chronic ischemic and non-ischemic cardiomyopathy patients.
Published in
Targeting immune-fibroblast cell communication in heart failure
Amrute JM, Luo X, Penna V et al. · Nature 2024 · PMID 39443792 · doi:10.1038/s41586-024-08008-5
This dataset
Open GSE217494 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE217494_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA899108 and SRA study SRP406759. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39443792) ↗
Study design
22 × GEX_sample vs 22 × Ab_sample

Supports a between-group comparison across 44 samples.

How we read this: 2 replicated groups read from 44 sample titles; they account for 44 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.

Samples in this study

+ 4 more — browse all 44 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.