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Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes and progenitors

GSE94820 Homo sapiens (human) Single-cell RNA-seq 2384 samples Submitted 2017/04/21 Platform GPL15520Platform GPL16791
At a glance

Single-cell RNA-seq · human · 2384 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
2384 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)
Peripheral blood mononuclear cells (PBMCs) were isolated from fresh blood using Ficoll-Paque density gradient centrifugation. Single-cell suspensions were stained with different antibody cocktails designed to enrich for particular immune cell populations, which were then single cell sorted in 96-well plates. Single cell RNA-sequencing libraries were subsequently generated for 2422 single cells using Smart-Seq2 (Picelli et al., Nature Methods, 2014). Cells were sequenced at a depth of 1-2M reads/cell.
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 GSE94820_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 PRJNA374527. Searching any of these in the dataset finder brings you back here.

Samples in this study

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