GEO series

HiChIP: Efficient and sensitive analysis of protein-directed genome architecture

GSE80820 Homo sapiens (human) Other 18 samples Submitted 2016/08/31 Platform GPL20301Platform GPL21103

At a glance

human · 18 samples

Organism: Homo sapiens (human)
Samples: 18 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI.

Summary (written by the submitters)

Three-dimensional genome structure is central to gene control, but current technologies are often impractical for many biological questions due to cell and read number requirements. Here we present HiChIP, a protein-centric chromatin conformation method. HiChIP improves the fraction of conformation-informative reads by over 10-fold and lowers input requirement greater than 100-fold to 1 million cells.

Read the full summary ↓

HiChIP of cohesin reveals multi-scale genome architecture with greater signal to noise than in situ Hi-C. Thus, HiChIP will enable insight into the genome’s three-dimensional structure and regulation in once-inaccessible biological systems.

This dataset

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Download · which file do I need?

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 (GSE80820_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 PRJNA320090 and SRA study SRP074188. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27643841) ↗

Samples in this study

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