Evidence map›Paper›PMID 25522020›Full record

ArticleBMC genomics2014

dCaP: detecting differential binding events in multiple conditions and proteins.

Kuan-Bei Chen, Ross Hardison, Yu Zhang

Abstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. A MAD-Bayes Algorithm for State-Space Inference and Clustering with Application to Querying Large Collections of ChIP-Seq Data Sets.Journal of computational biology : a journal of computational molecular cell biology · 2017
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kuan-Bei Chen
Ross Hardison
Yu Zhang

Funding

Global Predictions and Tests of Erythroid RegulationR01DK065806 · NIDDK · PENNSYLVANIA STATE UNIVERSITY-UNIV PARK · PI BLOBEL, GERD A, CHIAROMONTE, FRANCESCA · 2004 to 2013
$5.3M
Enhance human ENCODE by function comparisons to mouseRC2HG005573 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI HARDISON, ROSS C · 2009 to 2011
$2.2M
New Bayesian algorithms for genome-wide association mappingR01HG004718 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI ZHANG, YU · 2008 to 2014
$964k
Global Predictions and Tests of Hematopoietic RegulationR56DK065806 · NIDDK · PENNSYLVANIA STATE UNIVERSITY, THE · PI BLOBEL, GERD A, BODINE, DAVID M. · 2014 to 2014
$224k
NHGRI NIH HHS R01 HG004718NHGRI NIH HHS R01 HG004718-04A1
6 · The paper itself

Abstract

backgroundCurrent ChIP-seq studies are interested in comparing multiple epigenetic profiles across several cell types and tissues simultaneously for studying constitutive and differential regulation. Simultaneous analysis of multiple epigenetic features in many samples can gain substantial power and specificity than analyzing individual features and/or samples separately. Yet there are currently few tools can perform joint inference of constitutive and differential regulation in multi-feature-multi-condition contexts with statistical testing. Existing tools either test regulatory variation for one factor in multiple samples at a time, or for multiple factors in one or two samples. Many of them only identify binary rather than quantitative variation, which are sensitive to threshold choices.

resultsWe propose a novel and powerful method called dCaP for simultaneously detecting constitutive and differential regulation of multiple epigenetic factors in multiple samples. Using simulation, we demonstrate the superior power of dCaP compared to existing methods. We then apply dCaP to two datasets from human and mouse ENCODE projects to demonstrate its utility. We show in the human dataset that the cell-type specific regulatory loci detected by dCaP are significantly enriched near genes with cell-type specific functions and disease relevance. We further show in the mouse dataset that dCaP captures genomic regions showing significant signal variations for TAL1 occupancy between two mouse erythroid cell lines. The novel TAL1 occupancy loci detected only by dCaP are highly enriched with GATA1 occupancy and differential gene expression, while those detected only by other methods are not.

conclusionsHere, we developed a novel approach to utilize the cooperative property of proteins to detect differential binding given multivariate ChIP-seq samples to provide better power, aiming for complementing existing approaches and providing new insights in the method development in this field.

Indexed as

Epigenesis, GeneticAnimalsCell Line, TumorComputational BiologyDNA Copy Number VariationsHumansLikelihood FunctionsMiceProtein BindingProteinsProteins

Identifiers

PMID25522020
PMCPMC4290593

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.