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Droplet barcoding for single cell transcriptomics applied to embryonic stem cells

GSE65525 Homo sapiens (human) Single-cell RNA-seq 8 samples Submitted 2015/05/20 Platform GPL16417Platform GPL17021Platform GPL18573Platform GPL19057Platform GPL16791
At a glance

Single-cell RNA-seq · human · 8 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
8 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)
Recently, RNA sequencing has achieved single cell resolution, but what is limiting is an effective way to routinely isolate and process large numbers of individual cells for in-depth sequencing, and to do so quantitatively. We have developed a droplet-microfluidic approach for parallel barcoding thousands of individual cells for subsequent RNA profiling by next-generation sequencing.
Read the full summary ↓
This high-throughput method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. Using this technique, we analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after LIF withdrawal. The reproducibility and low noise of this high-throughput single cell data allowed us to deconstruct cell populations and infer gene expression relationships.
This dataset
Open GSE65525 in finder → Find more 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 GSE65525_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 PRJNA274274 and SRA study SRP053052. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 26000487) ↗
Samples in this study

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+ 8 more — browse all 8 samples with per-sample file links →

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