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The dynamics of cellular response to therapeutic perturbation using multiplexed quantification of the proteome and transcriptome at single-cell resolution

GSE100501 Homo sapiens (human) Single-cell RNA-seq 31 samples Submitted 2017/08/28 Platform GPL16791
At a glance

Single-cell RNA-seq · human · 31 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
31 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)
We developed a scalable assay permitting the simultaneous quantification of hundreds of proteins and the full transcriptome in thousands of individual cells from samples where cell number is limiting. The RNA Expression and Protein Sequencing assay (REAP-seq) uses DNA-labeled antibodies to permit DNA sequencing of both mRNA and antibodies in a single workflow using droplet microfluidics.
Read the full summary ↓
We describe the development and validation of REAP-seq in human PBMCs, and use the assay to assess the costimulatory effects of an anti-CD27 agonist antibody in naïve CD8+ lymphocytes. Protein quantification using REAP-seq was more sensitive than parallel mRNA measurements and differentiated cell states with fewer analytes. Unbiased profiling of single cells without prior selection enabled identification and characterization of an unexpected cell type that would have been missed with population-averaged profiling methodologies.
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 GSE100501_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 PRJNA391958 and SRA study SRP110537. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 31 more — browse all 31 samples with per-sample file links →

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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.