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Single-cell RNA-seq of sort human lung explants from IPF and SSc-ILD patients

GSE159354 Homo sapiens (human) Single-cell RNA-seq 48 samples Submitted 2020/12/15 Platform GPL20301
At a glance

Single-cell RNA-seq · human · 48 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
48 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)
To understand the cellular composition and transcriptional phenotype of fibrotic lung tissue we performed single-cell RNA-seq on stromal, immune, epithelial, and endothelial cell populations from human lung explants. Tissue was collected from normal control lungs, patients with idiopathic pulmonary fibrosis (IPF), and patients with systemic sclerosis associated interstitial lung disease (SSc-ILD). Using the 10X Genomics Chromium platform, we generated transcriptional profiles of approximately 200,500 cells across 4 IPF, 3 SSc-ILD and 3 normal control lungs.
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 GSE159354_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 PRJNA668609 and SRA study SRP287014. Searching any of these in the dataset finder brings you back here.

Samples in this study

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