Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Interactive analysis of single-cell epigenomic landscapes with ChromSCape

ABSTRACT: Here, we present ChromSCape, a user-friendly interactive Shiny/R application that processes single-cell epigenomic data to help the biological interpretation of chromatin landscapes within cell populations. ChromSCape successfully analyses the distribution of repressive and active histone modifications as well as chromatin accessibility landscapes from single-cell datasets.

ORGANISM(S): Homo sapiens

PROVIDER: GSE152502 | GEO | 2020/06/16

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Interactive analysis of single-cell epigenomic landscapes with ChromSCape

Project description:Interactive analysis of single-cell epigenomic landscapes with ChromSCape

| PRJNA639548 | ENA

PeptideShaker - PeptideShaker is a user friendly tool for shotgun proteomic data interpretation and reprocessing.

Project description:PeptideShaker is a user friendly tool for shotgun proteomic data interpretation and reprocessing. The present dataset is the example dataset and consists of a single run HeLa measurement.

2014-01-27 | PXD000674 | Pride

PeptideShaker

2017-03-28 | MSV000080689 | MassIVE

Multifactorial chromatin regulatory landscapes at single cell resolution

Project description:Multifactorial chromatin regulatory landscapes at single cell resolution

| PRJNA744912 | ENA

4C-seq indicate interactive sites with the sequence close from Meis2 promoter

2014-01-15 | GSE52281 | GEO

4C-seq indicate interactive sites with the sequence close from Meis2 promoter

Project description:We report the distribution of interactive sites with the sequence close from Meis2 promoter within the genome of mouse embryonic forebrain. We prepared the chromatin from 11 dpc embryonic forebrain and made 3C (chromosomal conformation capture) library. High-throughput sequencing applied for the 3C analysis revealed the distribution of modified interactive sites within developing forebrain. 4C-seq analysis of mouse 11 dpc embryonic forebrain with the sequence close from Meis2 promoter. Forebrain isolated and disected from 11 dpc embryos are fixed by 1% formaldehyde. After conventional 3C reaction, 3C library for highthroughput sequence is prepared by combination of adaptor ligation and nesting PCR reactions.

2014-01-15 | E-GEOD-52281 | biostudies-arrayexpress

An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics

Project description:Aging promotes lung function decline and susceptibility to chronic lung diseases, which are the third leading cause of death worldwide. We used single cell transcriptomics and mass spectrometry to quantify changes in cellular activity states of 30 cell types and the tissue proteome from lungs of young and old mice. Aging led to increased transcriptional noise, indicating deregulated epigenetic control. We observed highly distinct effects of aging on cell type level, uncovering increased cholesterol biosynthesis in type-2 pneumocytes and lipofibroblasts as a novel hallmark of lung aging. Proteomic profiling revealed extracellular matrix remodeling in old mice, including increased collagen IV and XVI and decreased Fraser syndrome complex proteins and Collagen XIV. Computational integration of the aging proteome and single cell transcriptomes predicted the cellular source of regulated proteins and created a first unbiased reference of the aging lung. The lung aging atlas can be accessed via an interactive user-friendly webtool at: https://theislab.github.io/LungAgingAtlas

2019-01-21 | PXD012307 | Pride

HiCrayon reveals distinct layers of multi-state 3D chromatin organization

Project description:The co-visualization of chromatin conformation with 1D 'omics data is key to the multi-omics driven data analysis of 3D genome organization. Chromatin contact maps are often shown as 2D heatmaps and visually compared to 1D genomic data by simple juxtaposition. While common, this strategy is imprecise, placing the onus on the reader to align features with each other. To remedy this, we developed HiCrayon, an interactive tool that facilitates the integration of 3D chromatin organization maps and 1D datasets. This visualization method integrates data from genomic assays directly into the chromatin contact map by coloring interactions according to 1D signal. HiCrayon is implemented using R shiny and python to create a graphical user interface (GUI) application, available in both web or containerized format to promote accessibility. HiCrayon is implemented in R, and includes a graphical user interface (GUI), as well as a slimmed-down web-based version that lets users quickly produce publication-ready images. We demonstrate the utility of HiCrayon in visualizing the effectiveness of compartment calling and the relationship between ChIP-seq and various features of chromatin organization. We also demonstrate the improved visualization of other 3D genomic phenomena, such as differences between loops associated with CTCF/cohesin vs. those associated with H3K27ac. We then demonstrate HiCrayon's visualization of organizational changes that occur during differentiation and use HiCrayon to detect compartment patterns that cannot be assigned to either A or B compartments, revealing a distinct 3rd chromatin compartment. Overall, we demonstrate the utility of co-visualizing 2D chromatin conformation with 1D genomic signals within the same matrix to reveal fundamental aspects of genome organization.

2024-02-12 | GSE255264 | GEO

Chromatin accessibility landscapes across B-ALL

Project description:Chromatin accessibility landscapes across B-ALL

| PRJNA871228 | ENA

proteiNorm – A user-friendly tool for normalization and analysis of TMT and label-free protein quantification

Project description:The technological advances in mass spectrometry allow us to collect more comprehensive data with higher quality and increasing speed. With the rapidly increasing amount of data generated, the need for streamlining analyses becomes more apparent. Proteomic data is known to be often affected by systemic bias from unknown sources, and failing to adequately normalize the data can lead to erroneous conclusions. To allow researchers to easily evaluate and compare different normalization methods via a user-friendly interface, we have developed “proteiNorm”. The current implementation of proteiNorm accommodates preliminary filter on peptide and sample level, followed by an evaluation of several popular normalization methods and visualization of missing value. The user then selects an adequate normalization method and one of several imputation methods used for the subsequent comparison of different differential abundance/expression methods and estimation of statistical power. The application of proteiNorm and interpretation of its results is demonstrated on a Tandem Mass Tag mass spectrometry example data set, where the proteome of three different breast cancer cell lines was profiled with and without hydroxyurea treatment. With proteiNorm, we provide a user-friendly tool to identify an adequate normalization method and to select an appropriate method for a differential abundance/expression analysis.

2021-09-09 | PXD018152 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data