Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Retrieving high-resolution chromatin interactions and decoding enhancer regulatory potential in silico

ABSTRACT: Retrieving high-resolution chromatin interactions and decoding enhancer regulatory potential in silico

PROVIDER: PRJNA678980 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR13074119_1.fastq.gz	Fastqsanger.gz
	SRR13074119_2.fastq.gz	Fastqsanger.gz
	SRR13074120_1.fastq.gz	Fastqsanger.gz
	SRR13074120_2.fastq.gz	Fastqsanger.gz

Items per page:

1 - 4 of 4

Similar Datasets

Retrieving high-resolution chromatin interactions and decoding enhancer regulatory potential in silico

Project description:The advent of the chromosome conformation capture (3C) and related technologies has profoundly renewed our understaning of three-dimensional chromatin folding in mammalian nuclei. Alongside these experimental approaches, numerous computational tools for handling, normalizing, visualizing, and ultimately detecting interactions in 3C-type datasets are being developed. Here, we present Bloom, a comprehensive method for the analysis of 3C-type data matrices on the basis of Dirichlet process mixture models that addresses two important open issues. First, it retrieves occult interaction patterns from sparse data, like those derived from single-cell or “native” Hi-C experiments; thus, bloomed sparse data can now be used to study interaction landscapes at high-resolution. Second, it detects enhancer-promoter interactions with high sensitivity and inherently assigns an interaction frequency score (IFS) to each contact. Using enhancer perturbation data of different throughput, we show that IFS accurately quantifies the regulatory influence of each enhancer on its target promoter. As a result, Bloom allows decoding of complex regulatory landscapes by generating functionally-relevant enhancer atlases solely on the basis of 3C-type data.

2021-12-01 | GSE161636 | GEO

Decoding the transcriptome of denervated muscle at single-nucleus resolution

Project description:Decoding the transcriptome of denervated muscle at single-nucleus resolution

| PRJNA762034 | ENA

Decoding the transcriptome of calcified atherosclerotic plaque at single-cell resolution

Project description:Decoding the transcriptome of calcified atherosclerotic plaque at single-cell resolution

| PRJNA670178 | ENA

Decoding the endometrial niche of Asherman's syndrome at single-cell resolution

Project description:Decoding the endometrial niche of Asherman's syndrome at single-cell resolution

| PRJNA891357 | ENA

Decoding the endometrial niche of Asherman's syndrome at single-cell resolution [organoids]

Project description:Decoding the endometrial niche of Asherman's syndrome at single-cell resolution [organoids]

| PRJNA895089 | ENA

Decoding breast cancer tissue-stroma interactions using species-specific sequencing

Project description:Decoding genome-wide effects of experimental tissue-tissue or cell-cell interactions is important, for example, to better understand tumor-stroma interactions after transplantation (xenografting). Transcriptome analysis of intermixed human and mouse cells has frequently relied on the need to separate the two cell populations prior to transcriptome analysis, which introduces confounding effects on gene expression. To circumvent this problem, we perform a bioinformatics-based genome-wide transcriptome analysis technique separating the mouse and human transcriptome part of a dataset, which allows a mixed mouse and human cell population to be sequenced without prior cell sorting. We use the new technology – which we call S3 (“S-cube” for Species-specific sequencing) technology – to provide new insights into the Notch downstream response following Notch ligand-stimulation and to explore transcriptional changes following transplantation of luminal (MCF7) and basal-type (MDA-MB-231) human breast cancer cells into mammary fat pad tissue in mice. Analysis of Notch response to ligand in three settings: co-culture, immobilized ligand and xenografted tumors

2015-08-12 | E-GEOD-66744 | biostudies-arrayexpress

Decoding murine cytomegalovirus

Project description:Decoding murine cytomegalovirus

| PRJNA874807 | ENA

Decoding Human Megakaryocyte Development

Project description:Decoding Human Megakaryocyte Development

| PRJNA602526 | ENA

Decoding SFRP2hi Fibroblast Progenitors in Sustaining Tooth Growth in Humans and Mice at Single-Cell Resolution

Project description:Decoding SFRP2hi Fibroblast Progenitors in Sustaining Tooth Growth in Humans and Mice at Single-Cell Resolution

| PRJNA1149480 | ENA

in silico Serotyping

Project description:A set of 520 genomes where serotyped with two in silico typing tools