Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Input Strategy for Improving Analysis of ChIP-exo Data and Beyond

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE79565 | GEO | 2016/08/24

SECONDARY ACCESSION(S): PRJNA316188

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

PAtCh-Cap: input strategy for improving analysis of ChIP-exo data sets and beyond.

Project description:Recently, a number of advances have been implemented into the core ChIP-seq (chromatin immunoprecipitation coupled with next-generation sequencing) methodology to streamline the process, reduce costs or improve data resolution. Several of these emerging ChIP-based methods perform additional chemical steps on bead-bound immunoprecipitated chromatin, posing a challenge for generating similarly treated input controls required for artifact removal during bioinformatics analyses. Here we present a versatile method for producing technique-specific input controls for ChIP-based methods that utilize additional bead-bound processing steps. This reported method, termed protein attached chromatin capture (PAtCh-Cap), relies on the non-specific capture of chromatin-bound proteins via their carboxylate groups, leaving the DNA accessible for subsequent chemical treatments in parallel with chromatin separately immunoprecipitated for the target protein. Application of this input strategy not only significantly enhanced artifact removal from ChIP-exo data, increasing confidence in peak identification and allowing for de novo motif searching, but also afforded discovery of a novel CTCF binding motif.

| S-EPMC5137431 | biostudies-literature

Input Strategy for Improving Analysis of ChIP-exo Data and Beyond [RNA-Seq]

Project description:Several recently emerging ChIP-seq (chromatin immunoprecipitation followed by sequencing) based methods perform chemical steps on bead-bound immunoprecipitated chromatin, posing a challenge for generating similarly treated input controls required for bioinformatics and data quality analyses. Here we present a versatile method for producing technique-specific input controls for ChIP-based methods that utilize additional bead-bound processing steps. Application of this method allowed for discovery of a novel CTCF binding motif from ChIP-exo data.

2016-08-24 | GSE79564 | GEO

PAtCh-Cap: input strategy for improving analysis of ChIP-exo data sets and beyond

2016-08-24 | GSE79563 | GEO

Input Strategy for Improving Analysis of ChIP-exo Data and Beyond

Project description:Input Strategy for Improving Analysis of ChIP-exo Data and Beyond

| PRJNA316188 | ENA

ChIP-exo analysis of the DNA-binding sites of the yeast transcription factor Yfl052w

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2014-07-22 | E-GEOD-57902 | biostudies-arrayexpress

Impact of artifact removal on ChIP quality metrics in ChIP-seq and ChIP-exo data.

Project description:With the advent of ChIP-seq multiplexing technologies and the subsequent increase in ChIP-seq throughput, the development of working standards for the quality assessment of ChIP-seq studies has received significant attention. The ENCODE consortium's large scale analysis of transcription factor binding and epigenetic marks as well as concordant work on ChIP-seq by other laboratories has established a new generation of ChIP-seq quality control measures. The use of these metrics alongside common processing steps has however not been evaluated. In this study, we investigate the effects of blacklisting and removal of duplicated reads on established metrics of ChIP-seq quality and show that the interpretation of these metrics is highly dependent on the ChIP-seq preprocessing steps applied. Further to this we perform the first investigation of the use of these metrics for ChIP-exo data and make recommendations for the adaptation of the NSC statistic to allow for the assessment of ChIP-exo efficiency.

| S-EPMC3989762 | biostudies-literature

ltra-low-input native ChIP-seq and Whole genome bisulfite Sequencing data of four types mouse spermatogenesis

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-07-17 | GSE137744 | GEO

Targeting H3K4 methylation as a therapeutic strategy for Huntington's disease

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2013-07-18 | E-GEOD-48963 | biostudies-arrayexpress

Characterizing protein-DNA binding event subtypes in ChIP-exo data.

Project description:MotivationRegulatory proteins associate with the genome either by directly binding cognate DNA motifs or via protein-protein interactions with other regulators. Each recruitment mechanism may be associated with distinct motifs and may also result in distinct characteristic patterns in high-resolution protein-DNA binding assays. For example, the ChIP-exo protocol precisely characterizes protein-DNA crosslinking patterns by combining chromatin immunoprecipitation (ChIP) with 5' → 3' exonuclease digestion. Since different regulatory complexes will result in different protein-DNA crosslinking signatures, analysis of ChIP-exo tag enrichment patterns should enable detection of multiple protein-DNA binding modes for a given regulatory protein. However, current ChIP-exo analysis methods either treat all binding events as being of a uniform type or rely on motifs to cluster binding events into subtypes.ResultsTo systematically detect multiple protein-DNA interaction modes in a single ChIP-exo experiment, we introduce the ChIP-exo mixture model (ChExMix). ChExMix probabilistically models the genomic locations and subtype memberships of binding events using both ChIP-exo tag distribution patterns and DNA motifs. We demonstrate that ChExMix achieves accurate detection and classification of binding event subtypes using in silico mixed ChIP-exo data. We further demonstrate the unique analysis abilities of ChExMix using a collection of ChIP-exo experiments that profile the binding of key transcription factors in MCF-7 cells. In these data, ChExMix identifies possible recruitment mechanisms of FoxA1 and ERα, thus demonstrating that ChExMix can effectively stratify ChIP-exo binding events into biologically meaningful subtypes.Availability and implementationChExMix is available from https://github.com/seqcode/chexmix.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC6419906 | biostudies-literature

Translational validation of personalized treatment strategy based on genetic characteristics of glioblastoma

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2014-06-12 | E-GEOD-58401 | biostudies-arrayexpress