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Functional Characterisation of Active Enhancers in Human Astrocytes Using a High-throughput CRISPRi Screen

GSE236057 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2025/01/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 14 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
14 samples: 7 × NHA_CROPseq_LibGroups are read from the sample names, not from the paper. Check the list below.
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 used CROP-seq to perform a high-throughput, parallel screen of 979 candidate enhancer perturbations in normal human astrocytes (NHAs), a primary cell-line. We identified the target gene(s) for 145 of these candidates, which were enriched for transcription with eRNA, transcription factor footprinting, and superenhancer annotation. Most regulatory interactions were <50kb, targeting the nearest gene in ~50% of cases, but were not typically captured by eQTL or in silico predictions. These data elucidate the regulatory network of an understudied-but-crucial brain cell-type.
This dataset
Open GSE236057 in finder → Find more human 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 GSE236057_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA988514 and SRA study SRP446349. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 × NHA_CROPseq_Lib

Supports a between-group comparison across 7 samples.

How we read this: 1 replicated groups read from 14 sample titles; they account for 7 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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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.