ArticlePLoS computational biology2016
metagene Profiles Analyses Reveal Regulatory Element's Factor-Specific Recruitment Patterns.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed.
- A data-driven genome annotation approach for cassava.The Plant journal : for cell and molecular biology · 2024Article
- MetageneCluster: a Python package for filtering conflicting signal trends in metagene plots.BMC bioinformatics · 2024Article
- Bayesian inference of polymerase dynamics over the exclusion process.Royal Society open science · 2023Article
- Connectome and regulatory hubs of CAGE highly active enhancers.Scientific reports · 2023Article
- GFI1 tethers the NuRD complex to open and transcriptionally active chromatin in myeloid progenitors.Communications biology · 2021Article
- SOX10-regulated promoter use defines isoform-specific gene expression in Schwann cells.BMC genomics · 2020Article
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- Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression: identification of a modifier of breast cancer risk at locus 11q22.3.Breast cancer research and treatment · 2017Article
- Article
- The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data.BMC genomics · 2016Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of the general occupancy pattern of a protein. Here we present the R package metagene, the graphical interface Imetagene and the companion package similaRpeak. Together, they provide a framework to integrate, summarize and compare the ChIP-Seq enrichment signal from complex experimental designs. Those packages identify and quantify similarities or dissimilarities in patterns between large numbers of ChIP-Seq profiles. We used metagene to investigate the differential occupancy of regulatory factors at noncoding regulatory regions (promoters and enhancers) in relation to transcriptional activity in GM12878 B-lymphocytes. The relationships between occupancy patterns and transcriptional activity suggest two different mechanisms of action for transcriptional control: i) a "gradient effect" where the regulatory factor occupancy levels follow transcription and ii) a "threshold effect" where the regulatory factor occupancy levels max out prior to reaching maximal transcription. metagene, Imetagene and similaRpeak are implemented in R under the Artistic license 2.0 and are available on Bioconductor.
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Registered trials
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.