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Systematic mapping of functional enhancer-promoter connections with CRISPR interference

GSE87257 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2016/11/11 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 8 conditions, mostly in triplicateGroups 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)
Gene expression in mammals is regulated by noncoding elements that can impact physiology and disease, yet the functions and target genes of most noncoding elements remain unknown. We present a high-throughput approach that uses CRISPR interference (CRISPRi) to discover regulatory elements and identify their target genes. We assess >1 megabase (Mb) of sequence in the vicinity of 2 essential transcription factors, MYC and GATA1, and identify 9 distal enhancers that control gene expression and cellular proliferation.
Read the full summary ↓
Quantitative features of chromatin state and chromosome conformation distinguish the 7 enhancers that regulate MYC from other elements that do not, suggesting a strategy for predicting enhancer-promoter connectivity. This CRISPRi-based approach can be applied to dissect transcriptional networks and interpret the contributions of noncoding genetic variation to human disease.
This dataset
Open GSE87257 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 GSE87257_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 PRJNA343954 and SRA study SRP090317. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27708057) ↗
Study design
8 conditions, mostly in triplicate
GATA1TSS-Guide1 ×3 GATA1TSS-Guide2 ×3 NC-Guide1 ×3 NC-Guide2 ×3 NC-Guide3 ×3 NC-Guide4 ×3 eHDAC6-Guide1 ×3 eHDAC6-Guide2 ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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.