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      ChEA3: transcription factor enrichment analysis by orthogonal omics integration

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          Abstract

          Identifying the transcription factors (TFs) responsible for observed changes in gene expression is an important step in understanding gene regulatory networks. ChIP-X Enrichment Analysis 3 (ChEA3) is a transcription factor enrichment analysis tool that ranks TFs associated with user-submitted gene sets. The ChEA3 background database contains a collection of gene set libraries generated from multiple sources including TF–gene co-expression from RNA-seq studies, TF–target associations from ChIP-seq experiments, and TF–gene co-occurrence computed from crowd-submitted gene lists. Enrichment results from these distinct sources are integrated to generate a composite rank that improves the prediction of the correct upstream TF compared to ranks produced by individual libraries. We compare ChEA3 with existing TF prediction tools and show that ChEA3 performs better. By integrating the ChEA3 libraries, we illuminate general transcription factor properties such as whether the TF behaves as an activator or a repressor. The ChEA3 web-server is available from https://amp.pharm.mssm.edu/ChEA3.

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          Most cited references17

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          D³: Data-Driven Documents.

          Data-Driven Documents (D3) is a novel representation-transparent approach to visualization for the web. Rather than hide the underlying scenegraph within a toolkit-specific abstraction, D3 enables direct inspection and manipulation of a native representation: the standard document object model (DOM). With D3, designers selectively bind input data to arbitrary document elements, applying dynamic transforms to both generate and modify content. We show how representational transparency improves expressiveness and better integrates with developer tools than prior approaches, while offering comparable notational efficiency and retaining powerful declarative components. Immediate evaluation of operators further simplifies debugging and allows iterative development. Additionally, we demonstrate how D3 transforms naturally enable animation and interaction with dramatic performance improvements over intermediate representations. © 2010 IEEE
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            JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework

            Nucleic Acids Research (2017), https://doi.org/10.1093/nar/gkx1126 The above paper was corrected to add a reference to its companion paper: Chèneby, J., Gheorghe, M., Artufel, M., Mathelier, A., Ballester, B. (2017) ReMap 2018: An updated atlas of regulatory regions from an integrative analysis of DNA-binding ChIP-seq experiments. Nucleic Acids Res., doi: 10.1093/nar/gkx1092.
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              Highly expressed loci are vulnerable to misleading ChIP localization of multiple unrelated proteins.

              Chromatin immunoprecipitation (ChIP) is the gold-standard technique for localizing nuclear proteins in the genome. We used ChIP, in combination with deep sequencing (Seq), to study the genome-wide distribution of the Silent information regulator (Sir) complex in Saccharomyces cerevisiae. We analyzed ChIP-Seq peaks of the Sir2, Sir3, and Sir4 silencing proteins and discovered 238 unexpected euchromatic loci that exhibited enrichment of all three. Surprisingly, published ChIP-Seq datasets for the Ste12 transcription factor and the centromeric Cse4 protein indicated that these proteins were also enriched in the same euchromatic regions with the high Sir protein levels. The 238 loci, termed "hyper-ChIPable", were in highly expressed regions with strong polymerase II and polymerase III enrichment signals, and the correlation between transcription level and ChIP enrichment was not limited to these 238 loci but extended genome-wide. The apparent enrichment of various proteins at hyper-ChIPable loci was not a consequence of artifacts associated with deep sequencing methods, as confirmed by ChIP-quantitative PCR. The localization of unrelated proteins, including the entire silencing complex, to the most highly transcribed genes was highly suggestive of a technical issue with the immunoprecipitations. ChIP-Seq on chromatin immunoprecipitated with a nuclear-localized GFP reproduced the above enrichment in an expression-dependent manner: induction of the GAL genes resulted in an increased ChIP signal of the GFP protein at these loci, with presumably no biological relevance. Whereas ChIP is a broadly valuable technique, some published conclusions based upon ChIP procedures may merit reevaluation in light of these findings.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                02 July 2019
                22 May 2019
                22 May 2019
                : 47
                : W1
                : W212-W224
                Affiliations
                Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 212 241 1153; Email: avi.maayan@ 123456mssm.edu
                Author information
                http://orcid.org/0000-0002-2755-2097
                http://orcid.org/0000-0002-1415-1286
                http://orcid.org/0000-0002-6904-1017
                Article
                gkz446
                10.1093/nar/gkz446
                6602523
                31114921
                1ed76c44-b783-4b0e-8c67-983e04acaa67
                © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 09 May 2019
                : 08 May 2019
                : 06 March 2019
                Page count
                Pages: 13
                Funding
                Funded by: NIH 10.13039/100000002
                Award ID: U54-HL127624
                Award ID: U24-CA224260
                Award ID: T32-GM062754
                Award ID: OT3-OD025467
                Categories
                Web Server Issue

                Genetics
                Genetics

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