GEO series

Dissecting immune circuits by linking CRISPR pooled screens with single cell RNA-seq [SET1]

GSE90486 Mus musculus (mouse) Single-cell RNA-seq 62 samples Submitted 2016/12/16 Platform GPL19057

At a glance

Single-cell RNA-seq · mouse · 62 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 62 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.
Paper: Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-SeqCell · 2016

Summary (written by the submitters)

In multicellular organisms, dedicated regulatory circuits control cell-type diversity and response. The crosstalk and redundancies within these circuits and substantial cellular heterogeneity pose a major research challenge. We present CRISP-seq, an integrated method for massively parallel single-cell RNA-seq and CRISPR pooled screens.

Read the full summary ↓

We show that profiling the perturbation and transcriptome in the same cell, enables to elucidate, the function of multiple factors and their interactions. In this benchmarking study, we applied this technology to probe regulatory circuits of innate immunity. By sampling tens of thousands of perturbed cells in vitro and in mice, we identified interactions and redundancies between developmental and signaling-dependent factors controlling the commitment toward different cell lineages or the inflammatory and antiviral pathways. CRISP-seq thereby emerges as a broadly applicable, comprehensive, and unbiased approach for elucidating mammalian regulatory circuits.

Published in

Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq

Jaitin DA, Weiner A, Yofe I et al. · Cell 2016 · PMID 27984734 · doi:10.1016/j.cell.2016.11.039

This dataset

Open GSE90486 in finder → Find more mouse 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 GSE90486_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 PRJNA354870 and SRA study SRP093880. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27984734) ↗

Samples in this study

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+ 62 more — browse all 62 samples with per-sample file links →

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