Literature DB >> 23629520

Batch effects and pathway analysis: two potential perils in cancer studies involving DNA methylation array analysis.

Kristin N Harper1, Brandilyn A Peters, Mary V Gamble.   

Abstract

BACKGROUND: DNA methylation microarrays have become an increasingly popular means of studying the role of epigenetics in cancer, although the methods used to analyze these arrays are still being developed and existing methods are not always widely disseminated among microarray users.
METHODS: We investigated two problems likely to confront DNA methylation microarray users: (i) batch effects and (ii) the use of widely available pathway analysis software to analyze results. First, DNA taken from individuals exposed to low and high levels of drinking water arsenic were plated twice on Illumina's Infinium 450 K HumanMethylation Array, once in order of exposure and again following randomization. Second, we conducted simulations in which random CpG sites were drawn from the 450 K array and subjected to pathway analysis using Ingenuity's IPA software.
RESULTS: The majority of differentially methylated CpG sites identified in Run One were due to batch effects; few sites were also identified in Run Two. In addition, the pathway analysis software reported many significant associations between our data, randomly drawn from the 450 K array, and various diseases and biological functions.
CONCLUSIONS: These analyses illustrate the pitfalls of not properly controlling for chip-specific batch effects as well as using pathway analysis software created for gene expression arrays to analyze DNA methylation array data. IMPACT: We present evidence that (i) chip-specific effects can simulate plausible differential methylation results and (ii) popular pathway analysis software developed for expression arrays can yield spurious results when used in tandem with methylation microarrays.

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Year:  2013        PMID: 23629520      PMCID: PMC3687782          DOI: 10.1158/1055-9965.EPI-13-0114

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  26 in total

1.  Comparison of different normalization assumptions for analyses of DNA methylation data from the cancer genome.

Authors:  Dong Wang; Yuannv Zhang; Yan Huang; Pengfei Li; Mingyue Wang; Ruihong Wu; Lixin Cheng; Wenjing Zhang; Yujing Zhang; Bin Li; Chenguang Wang; Zheng Guo
Journal:  Gene       Date:  2012-07-04       Impact factor: 3.688

2.  Adjusting batch effects in microarray expression data using empirical Bayes methods.

Authors:  W Evan Johnson; Cheng Li; Ariel Rabinovic
Journal:  Biostatistics       Date:  2006-04-21       Impact factor: 5.899

3.  On the design and analysis of gene expression studies in human populations.

Authors:  Joshua M Akey; Shameek Biswas; Jeffrey T Leek; John D Storey
Journal:  Nat Genet       Date:  2007-07       Impact factor: 38.330

4.  Run batch effects potentially compromise the usefulness of genomic signatures for ovarian cancer.

Authors:  Keith A Baggerly; Kevin R Coombes; E Shannon Neeley
Journal:  J Clin Oncol       Date:  2008-03-01       Impact factor: 44.544

5.  An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer.

Authors:  Holly K Dressman; Andrew Berchuck; Gina Chan; Jun Zhai; Andrea Bild; Robyn Sayer; Janiel Cragun; Jennifer Clarke; Regina S Whitaker; Lihua Li; Jonathan Gray; Jeffrey Marks; Geoffrey S Ginsburg; Anil Potti; Mike West; Joseph R Nevins; Johnathan M Lancaster
Journal:  J Clin Oncol       Date:  2007-02-10       Impact factor: 44.544

6.  Distinct physiological states of Plasmodium falciparum in malaria-infected patients.

Authors:  J P Daily; D Scanfeld; N Pochet; K Le Roch; D Plouffe; M Kamal; O Sarr; S Mboup; O Ndir; D Wypij; K Levasseur; E Thomas; P Tamayo; C Dong; Y Zhou; E S Lander; D Ndiaye; D Wirth; E A Winzeler; J P Mesirov; A Regev
Journal:  Nature       Date:  2007-11-28       Impact factor: 49.962

7.  OSAT: a tool for sample-to-batch allocations in genomics experiments.

Authors:  Li Yan; Changxing Ma; Dan Wang; Qiang Hu; Maochun Qin; Jeffrey M Conroy; Lara E Sucheston; Christine B Ambrosone; Candace S Johnson; Jianmin Wang; Song Liu
Journal:  BMC Genomics       Date:  2012-12-10       Impact factor: 3.969

8.  Batch effect correction for genome-wide methylation data with Illumina Infinium platform.

Authors:  Zhifu Sun; High Seng Chai; Yanhong Wu; Wendy M White; Krishna V Donkena; Christopher J Klein; Vesna D Garovic; Terry M Therneau; Jean-Pierre A Kocher
Journal:  BMC Med Genomics       Date:  2011-12-16       Impact factor: 3.063

9.  Methylation markers of early-stage non-small cell lung cancer.

Authors:  Kaie Lokk; Tõnu Vooder; Raivo Kolde; Kristjan Välk; Urmo Võsa; Retlav Roosipuu; Lili Milani; Krista Fischer; Marina Koltsina; Egon Urgard; Tarmo Annilo; Andres Metspalu; Neeme Tõnisson
Journal:  PLoS One       Date:  2012-06-29       Impact factor: 3.240

10.  DNA methylation arrays as surrogate measures of cell mixture distribution.

Authors:  Eugene Andres Houseman; William P Accomando; Devin C Koestler; Brock C Christensen; Carmen J Marsit; Heather H Nelson; John K Wiencke; Karl T Kelsey
Journal:  BMC Bioinformatics       Date:  2012-05-08       Impact factor: 3.169

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  37 in total

1.  Cross-sectional and longitudinal changes in DNA methylation with age: an epigenome-wide analysis revealing over 60 novel age-associated CpG sites.

Authors:  Ines Florath; Katja Butterbach; Heiko Müller; Melanie Bewerunge-Hudler; Hermann Brenner
Journal:  Hum Mol Genet       Date:  2013-10-26       Impact factor: 6.150

2.  Don't brush off buccal data heterogeneity.

Authors:  Andrei L Turinsky; Darci T Butcher; Sanaa Choufani; Rosanna Weksberg; Michael Brudno
Journal:  Epigenetics       Date:  2019-03-01       Impact factor: 4.528

Review 3.  Influence of environmental exposure on human epigenetic regulation.

Authors:  Carmen J Marsit
Journal:  J Exp Biol       Date:  2015-01-01       Impact factor: 3.312

4.  Differential DNA methylation and PM2.5 species in a 450K epigenome-wide association study.

Authors:  Lingzhen Dai; Amar Mehta; Irina Mordukhovich; Allan C Just; Jincheng Shen; Lifang Hou; Petros Koutrakis; David Sparrow; Pantel S Vokonas; Andrea A Baccarelli; Joel D Schwartz
Journal:  Epigenetics       Date:  2016-12-16       Impact factor: 4.528

5.  Epigenome-wide association of PTSD from heterogeneous cohorts with a common multi-site analysis pipeline.

Authors:  Andrew Ratanatharathorn; Marco P Boks; Adam X Maihofer; Allison E Aiello; Ananda B Amstadter; Allison E Ashley-Koch; Dewleen G Baker; Jean C Beckham; Evelyn Bromet; Michelle Dennis; Melanie E Garrett; Elbert Geuze; Guia Guffanti; Michael A Hauser; Varun Kilaru; Nathan A Kimbrel; Karestan C Koenen; Pei-Fen Kuan; Mark W Logue; Benjamin J Luft; Mark W Miller; Colter Mitchell; Nicole R Nugent; Kerry J Ressler; Bart P F Rutten; Murray B Stein; Eric Vermetten; Christiaan H Vinkers; Nagy A Youssef; Monica Uddin; Caroline M Nievergelt; Alicia K Smith
Journal:  Am J Med Genet B Neuropsychiatr Genet       Date:  2017-07-10       Impact factor: 3.568

6.  MBD-seq - realities of a misunderstood method for high-quality methylome-wide association studies.

Authors:  Karolina A Aberg; Robin F Chan; Edwin J C G van den Oord
Journal:  Epigenetics       Date:  2019-11-25       Impact factor: 4.528

7.  Arsenic exposure and human blood DNA methylation and hydroxymethylation profiles in two diverse populations from Bangladesh and Spain.

Authors:  Arce Domingo-Relloso; Anne Bozack; Samara Kiihl; Zulema Rodriguez-Hernandez; Pilar Rentero-Garrido; J Antonio Casasnovas; Montserrat Leon-Latre; Tamara Garcia-Barrera; J Luis Gomez-Ariza; Belen Moreno; Ana Cenarro; Griselda de Marco; Faruque Parvez; Abu B Siddique; Hasan Shahriar; Mohammad N Uddin; Tariqul Islam; Ana Navas-Acien; Mary Gamble; Maria Tellez-Plaza
Journal:  Environ Res       Date:  2021-09-10       Impact factor: 6.498

8.  Recurrent patterns of DNA methylation in the ZNF154, CASP8, and VHL promoters across a wide spectrum of human solid epithelial tumors and cancer cell lines.

Authors:  Francisco Sánchez-Vega; Valer Gotea; Hanna M Petrykowska; Gennady Margolin; Thomas C Krivak; Julie A DeLoia; Daphne W Bell; Laura Elnitski
Journal:  Epigenetics       Date:  2013-10-22       Impact factor: 4.528

9.  Exposure to aflatoxin B1 in utero is associated with DNA methylation in white blood cells of infants in The Gambia.

Authors:  Hector Hernandez-Vargas; Jovita Castelino; Matt J Silver; Paula Dominguez-Salas; Marie-Pierre Cros; Geoffroy Durand; Florence Le Calvez-Kelm; Andrew M Prentice; Christopher P Wild; Sophie E Moore; Branwen J Hennig; Zdenko Herceg; Yun Yun Gong; Michael N Routledge
Journal:  Int J Epidemiol       Date:  2015-04-07       Impact factor: 7.196

Review 10.  Epigenomics and allergic disease.

Authors:  Gabrielle A Lockett; Veeresh K Patil; Nelís Soto-Ramírez; Ali H Ziyab; John W Holloway; Wilfried Karmaus
Journal:  Epigenomics       Date:  2013-12       Impact factor: 4.778

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