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Interactive DNA Methylation Array Analysis with ShinyÉPICo

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Computational Epigenomics and Epitranscriptomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2624))

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Abstract

Arrays provide a cost-effective platform for the analysis of human DNA methylation. ShinyÉPICo is an interactive, web-based, and graphical tool that allows the user to analyze Illumina DNA methylation arrays (450 k and EPIC), from the user’s own computer or from a server. This tool covers the analysis entirely, from the raw data input to the final list of differentially methylated positions or regions. Here, we describe the steps of the analysis, the different parameters available, and useful information to understand and select the best options in each step.

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References

  1. Goldberg AD, Allis CD, Bernstein E (2007) Epigenetics: a landscape takes shape. Cell 128:635–638. https://doi.org/10.1016/j.cell.2007.02.006

    Article  CAS  PubMed  Google Scholar 

  2. de la Calle-Fabregat C, Morante-Palacios O, Ballestar E (2020) Understanding the relevance of DNA methylation changes in immune differentiation and disease. Genes (Basel) 11. https://doi.org/10.3390/genes11010110

  3. Jones PA (2012) Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet 13:484–492. https://doi.org/10.1038/nrg3230

    Article  CAS  PubMed  Google Scholar 

  4. Lev Maor G, Yearim A, Ast G (2015) The alternative role of DNA methylation in splicing regulation. Trends Genet 31:274–280

    Article  CAS  PubMed  Google Scholar 

  5. Chow JC, Yen Z, Ziesche SM, Brown CJ (2005) Silencing of the mammalian X chromosome. Annu Rev Genomics Hum Genet 6:69–92

    Article  CAS  PubMed  Google Scholar 

  6. Lister R, Pelizzola M, Dowen RH et al (2009) Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462:315–322. https://doi.org/10.1038/nature08514

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Neri F, Rapelli S, Krepelova A et al (2017) Intragenic DNA methylation prevents spurious transcription initiation. Nature 543:72–77. https://doi.org/10.1038/nature21373

    Article  CAS  PubMed  Google Scholar 

  8. Smith ML, Baggerly KA, Bengtsson H et al (2013) Illuminaio: an open source IDAT parsing tool for Illumina microarrays. F1000Research 2:264. https://doi.org/10.12688/f1000research.2-264.v1

    Article  PubMed  PubMed Central  Google Scholar 

  9. Aryee MJ, Jaffe AE, Corrada-Bravo H et al (2014) Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 30:1363–1369. https://doi.org/10.1093/bioinformatics/btu049

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Müller F, Scherer M, Assenov Y et al (2019) RnBeads 2.0: comprehensive analysis of DNA methylation data. Genome Biol 20:55. https://doi.org/10.1186/s13059-019-1664-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Ritchie ME, Phipson B, Wu D et al (2015) Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43:e47. https://doi.org/10.1093/nar/gkv007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Du P, Kibbe WA, Lin SM (2008) lumi: a pipeline for processing Illumina microarray. Bioinformatics 24:1547–1548. https://doi.org/10.1093/bioinformatics/btn224

    Article  CAS  PubMed  Google Scholar 

  13. Morante-Palacios O, Ballestar E (2021) shinyÉPICo: a graphical pipeline to analyze Illumina DNA methylation arrays. Bioinformatics. https://doi.org/10.1093/bioinformatics/btaa1095

  14. Ritchie ME, Diyagama D, Neilson J et al (2006) Empirical array quality weights in the analysis of microarray data. BMC Bioinf 7:261. https://doi.org/10.1186/1471-2105-7-261

    Article  CAS  Google Scholar 

  15. Law CW, Chen Y, Shi W, Smyth GK (2014) Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15:R29. https://doi.org/10.1186/gb-2014-15-2-r29

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Phipson B, Lee S, Majewski IJ et al (2016) Robust hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression. Ann Appl Stat 10:946–963. https://doi.org/10.1214/16-AOAS920

    Article  PubMed  PubMed Central  Google Scholar 

  17. Martorell-Marugán J, González-Rumayor V, Carmona-Sáez P (2019) MCSEA: detecting subtle differentially methylated regions. Bioinformatics 35:3257–3262. https://doi.org/10.1093/bioinformatics/btz096

    Article  CAS  PubMed  Google Scholar 

  18. McLean CY, Bristor D, Hiller M et al (2010) GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol 28:495–501. https://doi.org/10.1038/nbt.1630

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Heinz S, Benner C, Spann N et al (2010) Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 38:576–589. https://doi.org/10.1016/j.molcel.2010.05.004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

O.M.-P. holds an i-PFIS PhD Fellowship [IFI17/00034] from Acción Estratégica en Salud 2013–2016 ISCIII, co-financed by Fondo Social Europeo.

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Authors and Affiliations

  1. Epigenetics and Immune Disease Group, Josep Carreras Research Institute (IJC), Barcelona, Spain

    Octavio Morante-Palacios

  2. Germans Trias i Pujol Research Institute (IGTP), Barcelona, Spain

    Octavio Morante-Palacios

Authors
  1. Octavio Morante-Palacios
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Editor information

Editors and Affiliations

  1. Genoscope, Évry, France

    Pedro H. Oliveira

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© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Morante-Palacios, O. (2023). Interactive DNA Methylation Array Analysis with ShinyÉPICo. In: Oliveira, P.H. (eds) Computational Epigenomics and Epitranscriptomics. Methods in Molecular Biology, vol 2624. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2962-8_2

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  • DOI: https://doi.org/10.1007/978-1-0716-2962-8_2

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2961-1

  • Online ISBN: 978-1-0716-2962-8

  • eBook Packages: Springer Protocols

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