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Enhanced CLIP (eCLIP) enables robust and scalable transcriptome-wide discovery and characterization of RNA binding protein binding sites [eCLIP - HepG2/K562 cells]

GSE80039 Homo sapiens (human) Other 63 samples Submitted 2016/04/07 Platform GPL16791
At a glance

human · 63 samples

Organism
Homo sapiens (human)
Samples
63 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI.
Summary (written by the submitters)
RNA binding proteins (RBPs) play essential roles in cellular physiology by interacting with target RNAs. As defects in protein-RNA recognition lead to human disease, UV-crosslinking and immunoprecipitation (CLIP) of ribonuclear complexes followed by deep sequencing (-seq) is critical in constructing protein-RNA maps to expand our understanding of RBP function.
Read the full summary ↓
However, current CLIP protocols are technically demanding and involve low complexity libraries that yield squandered sequencing of PCR duplicates and high experimental failure rates. To enable truly large-scale implementation of CLIP-seq, we have developed an enhanced CLIP methodology (eCLIP) that features a decrease of ~10 cycles of requisite amplification with a concomitant >60% decrease in discarded PCR duplicate reads, while maintaining the ability to identify RNA binding with single-nucleotide resolution. By simplifying the generation of paired IgG and size-matched input controls, eCLIP also dramatically improves specificity in discovery of authentic binding sites. To demonstrate that eCLIP enables large-scale and robust profiling of RBPs, 102 eCLIP experiments in biological duplicate for a diverse collection of 74 RBPs in HepG2 and K562 cells were completed (available at https://www.encodeproject.org). We establish that eCLIP is comparable in amplification and sample requirements to ChIP-seq, and enables integrative analysis of diverse RBPs to reveal factor-specific profiles, common artifacts for CLIP experiments and RNA-centric perspectives of RBP activity.
This dataset
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Direct links to NCBI, 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.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE80039_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

Also filed as BioProject PRJNA317675 and SRA study SRP072994. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27018577) ↗
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