ArticleNucleic acids research2012
POLYPHEMUS: R package for comparative analysis of RNA polymerase II ChIP-seq profiles by non-linear normalization.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Epimetheus - a multi-profile normalizer for epigenomic sequencing data.BMC bioinformatics · 2017Article
- Reconstructed cell fate-regulatory programs in stem cells reveal hierarchies and key factors of neurogenesis.Genome research · 2016Article
- A comprehensive map of genome-wide gene regulation in Mycobacterium tuberculosis.Scientific data · 2015Article
- Characterising ChIP-seq binding patterns by model-based peak shape deconvolution.BMC genomics · 2013Article
- Accounting for immunoprecipitation efficiencies in the statistical analysis of ChIP-seq data.BMC bioinformatics · 2013Article
- A co-localization model of paired ChIP-seq data using a large ENCODE data set enables comparison of multiple samples.Nucleic acids research · 2013Article
- Practical guidelines for the comprehensive analysis of ChIP-seq data.PLoS computational biology · 2013Article
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4 authors.
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Abstract
Chromatin immunoprecipitation coupled with massive parallel sequencing (ChIP-seq) is increasingly used to map protein-chromatin interactions at global scale. The comparison of ChIP-seq profiles for RNA polymerase II (PolII) established in different biological contexts, such as specific developmental stages or specific time-points during cell differentiation, provides not only information about the presence/accumulation of PolII at transcription start sites (TSSs) but also about functional features of transcription, including PolII stalling, pausing and transcript elongation. However, annotation and normalization tools for comparative studies of multiple samples are currently missing. Here, we describe the R-package POLYPHEMUS, which integrates TSS annotation with PolII enrichment over TSSs and coding regions, and normalizes signal intensity profiles. Thereby POLYPHEMUS facilitates to extract information about global PolII action to reveal changes in the functional state of genes. We validated POLYPHEMUS using a kinetic study on retinoic acid-induced differentiation and a publicly available data set from a comparative PolII ChIP-seq profiling in Caenorhabditis elegans. We demonstrate that POLYPHEMUS corrects the data sets by normalizing for technical variation between samples and reveal the potential of the algorithm in comparing multiple data sets to infer features of transcription regulation from dynamic PolII binding profiles.
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