IDEAS home Printed from https://ideas.repec.org/a/spr/stabio/v8y2016i2d10.1007_s12561-016-9145-0.html
   My bibliography  Save this article

Statistical Challenges in Analyzing Methylation and Long-Range Chromosomal Interaction Data

Author

Listed:
  • Zhaohui Qin

    (Emory University)

  • Ben Li

    (Emory University)

  • Karen N. Conneely

    (Emory University School of Medicine)

  • Hao Wu

    (Emory University)

  • Ming Hu

    (New York University School of Medicine)

  • Deepak Ayyala

    (The Ohio State University)

  • Yongseok Park

    (University of Pittsburgh)

  • Victor X. Jin

    (The University of Texas Health Science Center at San Antonio)

  • Fangyuan Zhang

    (Texas Tech University)

  • Han Zhang

    (The Ohio State University)

  • Li Li

    (Emory University)

  • Shili Lin

    (The Ohio State University)

Abstract

With the rapid development of high-throughput technologies such as array and next generation sequencing, genome-wide, nucleotide-resolution epigenomic data are increasingly available. In recent years, there has been particular interest in data on DNA methylation and 3-dimensional (3D) chromosomal organization, which are believed to hold keys to understand biological mechanisms, such as transcription regulation, that are closely linked to human health and diseases. However, small sample size, complicated correlation structure, substantial noise, biases, and uncertainties, all present difficulties for performing statistical inference. In this review, we present an overview of the new technologies that are frequently utilized in studying DNA methylation and 3D chromosomal organization. We focus on reviewing recent developments in statistical methodologies designed for better interrogating epigenomic data, pointing out statistical challenges facing the field whenever appropriate.

Suggested Citation

  • Zhaohui Qin & Ben Li & Karen N. Conneely & Hao Wu & Ming Hu & Deepak Ayyala & Yongseok Park & Victor X. Jin & Fangyuan Zhang & Han Zhang & Li Li & Shili Lin, 2016. "Statistical Challenges in Analyzing Methylation and Long-Range Chromosomal Interaction Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 284-309, October.
    • Handle: RePEc:spr:stabio:v:8:y:2016:i:2:d:10.1007_s12561-016-9145-0
    DOI: 10.1007/s12561-016-9145-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12561-016-9145-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12561-016-9145-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fulai Jin & Yan Li & Jesse R. Dixon & Siddarth Selvaraj & Zhen Ye & Ah Young Lee & Chia-An Yen & Anthony D. Schmitt & Celso A. Espinoza & Bing Ren, 2013. "A high-resolution map of the three-dimensional chromatin interactome in human cells," Nature, Nature, vol. 503(7475), pages 290-294, November.
    2. Jeffrey T Leek & John D Storey, 2007. "Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis," PLOS Genetics, Public Library of Science, vol. 3(9), pages 1-12, September.
    3. Lindsay M. Reynolds & Jackson R. Taylor & Jingzhong Ding & Kurt Lohman & Craig Johnson & David Siscovick & Gregory Burke & Wendy Post & Steven Shea & David R. Jacobs Jr. & Hendrik Stunnenberg & Stephe, 2014. "Age-related variations in the methylome associated with gene expression in human monocytes and T cells," Nature Communications, Nature, vol. 5(1), pages 1-8, December.
    4. Danny Leung & Inkyung Jung & Nisha Rajagopal & Anthony Schmitt & Siddarth Selvaraj & Ah Young Lee & Chia-An Yen & Shin Lin & Yiing Lin & Yunjiang Qiu & Wei Xie & Feng Yue & Manoj Hariharan & Pradipta , 2015. "Integrative analysis of haplotype-resolved epigenomes across human tissues," Nature, Nature, vol. 518(7539), pages 350-354, February.
    5. Jesse R. Dixon & Siddarth Selvaraj & Feng Yue & Audrey Kim & Yan Li & Yin Shen & Ming Hu & Jun S. Liu & Bing Ren, 2012. "Topological domains in mammalian genomes identified by analysis of chromatin interactions," Nature, Nature, vol. 485(7398), pages 376-380, May.
    6. Zhijun Duan & Mirela Andronescu & Kevin Schutz & Sean McIlwain & Yoo Jung Kim & Choli Lee & Jay Shendure & Stanley Fields & C. Anthony Blau & William S. Noble, 2010. "A three-dimensional model of the yeast genome," Nature, Nature, vol. 465(7296), pages 363-367, May.
    7. Xun Lan & Christopher Adams & Mark Landers & Miroslav Dudas & Daniel Krissinger & George Marnellos & Russell Bonneville & Maoxiong Xu & Junbai Wang & Tim H-M Huang & Gavin Meredith & Victor X Jin, 2011. "High Resolution Detection and Analysis of CpG Dinucleotides Methylation Using MBD-Seq Technology," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-11, July.
    8. Takashi Nagano & Yaniv Lubling & Tim J. Stevens & Stefan Schoenfelder & Eitan Yaffe & Wendy Dean & Ernest D. Laue & Amos Tanay & Peter Fraser, 2013. "Single-cell Hi-C reveals cell-to-cell variability in chromosome structure," Nature, Nature, vol. 502(7469), pages 59-64, October.
    9. Shawn J. Cokus & Suhua Feng & Xiaoyu Zhang & Zugen Chen & Barry Merriman & Christian D. Haudenschild & Sriharsa Pradhan & Stanley F. Nelson & Matteo Pellegrini & Steven E. Jacobsen, 2008. "Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning," Nature, Nature, vol. 452(7184), pages 215-219, March.
    10. Nishanth Ulhas Nair & Avinash Das Sahu & Philipp Bucher & Bernard M E Moret, 2012. "ChIPnorm: A Statistical Method for Normalizing and Identifying Differential Regions in Histone Modification ChIP-seq Libraries," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-14, August.
    11. Dirk Schübeler, 2015. "Function and information content of DNA methylation," Nature, Nature, vol. 517(7534), pages 321-326, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ben Li & Yunxiao Li & Zhaohui S. Qin, 2017. "Improving Hierarchical Models Using Historical Data with Applications in High-Throughput Genomics Data Analysis," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 73-90, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang Qi & Xu Zheng & Lai Yutong, 2021. "An Empirical Bayes approach for the identification of long-range chromosomal interaction from Hi-C data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 20(1), pages 1-15, February.
    2. Guang Shi & D. Thirumalai, 2023. "A maximum-entropy model to predict 3D structural ensembles of chromatin from pairwise distances with applications to interphase chromosomes and structural variants," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. Surya K Ghosh & Daniel Jost, 2018. "How epigenome drives chromatin folding and dynamics, insights from efficient coarse-grained models of chromosomes," PLOS Computational Biology, Public Library of Science, vol. 14(5), pages 1-26, May.
    4. Ofir Shukron & David Holcman, 2017. "Transient chromatin properties revealed by polymer models and stochastic simulations constructed from Chromosomal Capture data," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-20, April.
    5. Yi Li & James Lee & Lu Bai, 2024. "DNA methylation-based high-resolution mapping of long-distance chromosomal interactions in nucleosome-depleted regions," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    6. Alon Diament & Tamir Tuller, 2015. "Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-22, May.
    7. Andrea Wilderman & Eva D’haene & Machteld Baetens & Tara N. Yankee & Emma Wentworth Winchester & Nicole Glidden & Ellen Roets & Jo Dorpe & Sandra Janssens & Danny E. Miller & Miranda Galey & Kari M. B, 2024. "A distant global control region is essential for normal expression of anterior HOXA genes during mouse and human craniofacial development," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    8. Seungsoo Hahn & Dongsup Kim, 2015. "Identifying and Reducing Systematic Errors in Chromosome Conformation Capture Data," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-17, December.
    9. Li-Hsin Chang & Sourav Ghosh & Andrea Papale & Jennifer M. Luppino & Mélanie Miranda & Vincent Piras & Jéril Degrouard & Joanne Edouard & Mallory Poncelet & Nathan Lecouvreur & Sébastien Bloyer & Amél, 2023. "Multi-feature clustering of CTCF binding creates robustness for loop extrusion blocking and Topologically Associating Domain boundaries," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    10. Yufan Zhou & Tian Li & Lavanya Choppavarapu & Kun Fang & Shili Lin & Victor X. Jin, 2024. "Integration of scHi-C and scRNA-seq data defines distinct 3D-regulated and biological-context dependent cell subpopulations," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    11. Zhen Wah Tan & Enrico Guarnera & Igor N Berezovsky, 2018. "Exploring chromatin hierarchical organization via Markov State Modelling," PLOS Computational Biology, Public Library of Science, vol. 14(12), pages 1-35, December.
    12. Peter H. Dixon & Adam P. Levine & Inês Cebola & Melanie M. Y. Chan & Aliya S. Amin & Anshul Aich & Monika Mozere & Hannah Maude & Alice L. Mitchell & Jun Zhang & Jenny Chambers & Argyro Syngelaki & Je, 2022. "GWAS meta-analysis of intrahepatic cholestasis of pregnancy implicates multiple hepatic genes and regulatory elements," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    13. Hao Wang & Jiaxin Yang & Yu Zhang & Jianliang Qian & Jianrong Wang, 2022. "Reconstruct high-resolution 3D genome structures for diverse cell-types using FLAMINGO," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    14. Dunming Hua & Ming Gu & Xiao Zhang & Yanyi Du & Hangcheng Xie & Li Qi & Xiangjun Du & Zhidong Bai & Xiaopeng Zhu & Dechao Tian, 2024. "DiffDomain enables identification of structurally reorganized topologically associating domains," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    15. Simeon Carstens & Michael Nilges & Michael Habeck, 2016. "Inferential Structure Determination of Chromosomes from Single-Cell Hi-C Data," PLOS Computational Biology, Public Library of Science, vol. 12(12), pages 1-33, December.
    16. Markus Götz & Olivier Messina & Sergio Espinola & Jean-Bernard Fiche & Marcelo Nollmann, 2022. "Multiple parameters shape the 3D chromatin structure of single nuclei at the doc locus in Drosophila," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    17. David E. Torres & H. Martin Kramer & Vittorio Tracanna & Gabriel L. Fiorin & David E. Cook & Michael F. Seidl & Bart P. H. J. Thomma, 2024. "Implications of the three-dimensional chromatin organization for genome evolution in a fungal plant pathogen," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    18. Sarah B. Reiff & Andrew J. Schroeder & Koray Kırlı & Andrea Cosolo & Clara Bakker & Luisa Mercado & Soohyun Lee & Alexander D. Veit & Alexander K. Balashov & Carl Vitzthum & William Ronchetti & Kent M, 2022. "The 4D Nucleome Data Portal as a resource for searching and visualizing curated nucleomics data," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    19. Zhen-Hui Wang & Xin-Feng Wang & Tianyuan Lu & Ming-Rui Li & Peng Jiang & Jing Zhao & Si-Tong Liu & Xue-Qi Fu & Jonathan F. Wendel & Yves Peer & Bao Liu & Lin-Feng Li, 2022. "Reshuffling of the ancestral core-eudicot genome shaped chromatin topology and epigenetic modification in Panax," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    20. Claudia Fierro & Veronica Gatti & Veronica Banca & Sara Domenico & Stefano Scalera & Giacomo Corleone & Maurizio Fanciulli & Francesca Nicola & Alessandro Mauriello & Manuela Montanaro & George A. Cal, 2023. "The long non-coding RNA NEAT1 is a ΔNp63 target gene modulating epidermal differentiation," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stabio:v:8:y:2016:i:2:d:10.1007_s12561-016-9145-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.