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Single cell RNA sequencing of valvular interstitial cells and adipose derived mesenchymal stem cells

GSE194180 Homo sapiens (human) Single-cell RNA-seq 1 samples Submitted 2022/01/24 Platform GPL18573
At a glance

Single-cell RNA-seq · human · 1 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
1 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)
A disease driver population within interstitial cells of human calcific aortic valves identified via single-cell and proteomic profiling Cellular heterogeneity of aortic valves complicates mechanistic evaluation of the calcification processes in calcific aortic valve disease (CAVD), and animal disease models are lacking. In this study, we identify a disease driver population (DDP) within valvular interstitial cells (VICs).
Read the full summary ↓
Through stepwise single-cell analysis, phenotype-guided -OMIC profiling, and network-based analysis, we characterize DDP fingerprint as CD44highCD29+CD59+CD73+CD45low and discover potential key regulators of human CAVD. These DDP-VICs demonstrate multi-lineage differentiation and osteogenic properties. Temporal proteomic profiling of DDP-VICs identifies potential targets for therapy, including MAOA and CTHRC1. In vitro loss-of-function experiments confirm our targets. Such a stepwise strategy may be advantageous for therapeutic target discovery in other disease contexts.
This dataset
Open GSE194180 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 GSE194180_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 PRJNA799367 and SRA study SRP356185. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

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