BayMeth:Improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach

Genome Biology

Volumn 15, Issue 2, 2014, Pages

  Riebler, Andrea ^a,b,c   Menigatti, Mirco ^a   Song, Jenny Z ^d   Statham, Aaron L ^d   Stirzaker, Clare ^d,e   Mahmud, Nadiya ^f   Mein, Charles A ^f   Clark, Susan J ^d,e   Robinson, Mark D ^a  

^a UNIVERSITY OF ZURICH   (Switzerland)

^b UNIVERSITY OF ZURICH   (Switzerland)

^c NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

^d GARVAN INSTITUTE OF MEDICAL RESEARCH   (Australia)

^e UNIVERSITY OF NEW SOUTH WALES   (Australia)

^f QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ATAXIN 1; CADHERIN; GAMMA GLUTAMYL HYDROLASE;

ALLELE; ANIMAL EXPERIMENT; ANIMAL MODEL; ARTICLE; ATAXIN 1 GENE; CADHERIN GENE; CATENIN ALPHA2 GENE; CONTROLLED STUDY; DESMOCOLLIN 3 GENE; DISEASE ASSOCIATION; DOBERMAN PINSCHER; GENE; GENE DELETION; GENE EXPRESSION; GENE IDENTIFICATION; GENE LOCUS; GENE SEQUENCE; GENE SILENCING; GENETIC ASSOCIATION; GENETIC VARIABILITY; HUMAN; HUMAN CELL; INDEL MUTATION; MISSENSE MUTATION; NONHUMAN; OBSESSIVE COMPULSIVE DISORDER; PLASMA GLUTAMATE CARBOXYPEPTIDASE GENE; PROTEIN DNA BINDING; REPORTER GENE; SINGLE NUCLEOTIDE POLYMORPHISM; SYNAPSE; BAYES THEOREM; COPY NUMBER VARIATION; CPG ISLAND; DNA METHYLATION; EVALUATION STUDY; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN GENOME; ALGORITHM; AUTOSOME; CALCULATION; DATA ANALYSIS; DATA ANALYSIS SOFTWARE; DNA SEQUENCE; EMBRYO; LINEAR SYSTEM; MALE; MATHEMATICAL MODEL; PREDICTION; PROSTATE EPITHELIUM CELL; QUANTITATIVE ANALYSIS;

BAYES THEOREM; CPG ISLANDS; DNA COPY NUMBER VARIATIONS; DNA METHYLATION; EVALUATION STUDIES AS TOPIC; GENOME, HUMAN; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS;

EID: 84897558199     PISSN: None     EISSN: 1474760X     Source Type: Journal    
DOI: 10.1186/gb-2014-15-2-r35     Document Type: Article

References (58)

1. Jones PA, Baylin SB. The epigenomics of cancer. Cell 2007, 128:683-692. 10.1016/j.cell.2007.01.029, 3894624, 17320506.
2. Slomko H, Heo HJ, Einstein FH. Minireview:epigenetics of obesity and diabetes in humans. Endocrinology 2012, 153:1025-1030. 10.1210/en.2011-1759, 3281541, 22253427.
3. Clark SJ, Melki J. DNA methylation and gene silencing in cancer:which is the guilty party?. Oncogene 2002, 21:5380-5387. 10.1038/sj.onc.1205598, 12154400.
4. Esteller M. Cancer epigenomics:DNA methylomes and histone-modification maps. Nat Rev Genet 2007, 8:286-298. 10.1038/nrg2005, 17339880.
5. Ziller MJ, Gu H, Müller F, Donaghey J, Tsai LTY, Kohlbacher O, De Jager PL, Rosen ED, Bennett DA, Bernstein BE, Gnirke A, Meissner A. Charting a dynamic DNA methylation landscape of the human genome. Nature 2013, 500:477-481. 10.1038/nature12433, 3821869, 23925113.
6. Ruike Y, Imanaka Y, Sato F, Shimizu K, Tsujimoto G. Genome-wide analysis of aberrant methylation in human breast cancer cells using methyl-DNA immunoprecipitation combined with high-throughput sequencing. BMC Genomics 2010, 11:137. 10.1186/1471-2164-11-137, 2838848, 20181289.
7. Stein RA. Epigenetics - the link between infectious diseases and cancer. J Am Med Assoc 2011, 305:1484-1485.
8. Baylin SB, Jones PA. A decade of exploring the cancer epigenome - biological and translational implications. Nat Rev Cancer 2011, 11:726-734. 10.1038/nrc3130, 3307543, 21941284.
9. Jones PA. Functions of DNA methylation:islands, start sites, gene bodies and beyond. Nat Rev Genet 2012, 13:484-492. 10.1038/nrg3230, 22641018.
10. Gu H, Bock C, Mikkelsen TS, Jager N, Smith ZD, Tomazou E, Gnirke A, Lander ES, Meissner A. Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution. Nature Methods 2010, 7:133-136. 10.1038/nmeth.1414, 2860480, 20062050.
11. Laird PW. Principles and challenges of genome-wide DNA methylation analysis. Nat Rev Genet 2010, 11:191-203. 10.1038/nrg2732, 20125086.
12. Lister R, Ecker JR. Finding the fifth base:genome-wide sequencing of cytosine methylation. Genome Res 2009, 19:959-966. 10.1101/gr.083451.108, 3807530, 19273618.
13. Kerick M, Fischer A, Schweiger MR. Generation and analysis of genome-wide DNA methylation maps. Bioinformatics for High Throughput Sequencing 2012, 151-167. New York:Springer, Rodríguez-Ezpeleta N, Hackenberg M, Aransay AM.
14. Clark SJ, Harrison J, Paul CL, Frommer M. High sensitivity mapping of methylated cytosines. Nucleic Acids Res 1994, 22:2990-2997. 10.1093/nar/22.15.2990, 310266, 8065911.
15. Bibikova M, Barnes B, Tsan C, Ho V, Klotzle B, Le JM, Delano D, Zhang L, Schroth GP, Gunderson KL, Fan JB, Shen R. High density DNA methylation array with single CpG site resolution. Genomics 2011, 98:288-295. 10.1016/j.ygeno.2011.07.007, 21839163.
16. Robinson MD, Statham AL, Speed TP, Clark SJ. Protocol matters:which metylome are you actually studying?. Epigenomics 2010, 2:587-598. 10.2217/epi.10.36, 3090160, 21566704.
17. Hansen KD, Timp W, Bravo HC, Sabunciyan S, Langmead B, McDonald OG, Wen B, Wu H, Liu Y, Diep D, Briem E, Zhang K, Irizarry RA, Feinberg AP. Increased methylation variation in epigenetic domains across cancer types. Nat Genet 2011, 43:768-775. 10.1038/ng.865, 3145050, 21706001.
18. Lee EJ, Pei L, Srivastava G, Joshi T, Kushwaha G, Choi JH, Robertson KD, Wang X, Colbourne JK, Zhang L, Schroth GP, Xu D, Zhang K, Shi H. Targeted bisulfite sequencing by solution hybrid selection and massively parallel sequencing. Nucleic Acids Res 2011, 39:e127. 10.1093/nar/gkr598, 3201883, 21785137.
19. Lee EJ, Luo J, Wilson JM, Shi H. Analyzing the cancer methylome through targeted bisulfite sequencing. Cancer Lett 2013, 340:171-178. 10.1016/j.canlet.2012.10.040, 23200671.
20. Clarke J, Wu HC, Jayasinghe L, Patel A, Reid S, Bayley H. Continuous base identification for single-molecule nanopore DNA sequencing. Nat Nanotechnol 2009, 4:265-270. 10.1038/nnano.2009.12, 19350039.
21. Flusberg BA, Webster DR, Lee JH, Travers KJ, Olivares EC, Clark TA, Korlach J, Turner SW. Direct detection of DNA methylation during single-molecule, real-time sequencing. Nat Methods 2010, 7:461-465. 10.1038/nmeth.1459, 2879396, 20453866.
22. Down TA, Rakyan VK, Turner DJ, Flicek P, Li H, Kulesha E, Gräf S, Johnson N, Herrero J, Tomazou EM, Thorne NP, Bäckdahl L, Herberth M, Howe KL, Jackson DK, Miretti MM, Marioni JC, Birney E, Hubbard TJP, Durbin R, Tavaré S, Beck S. A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis. Nat Biotechnol 2008, 26:779-785. 10.1038/nbt1414, 2644410, 18612301.
23. Aberg KA, McClay JL, Nerella S, Xie LY, Clark SL, Hudson AD, Bukszár J, Adkins D, Hultman CM, Sullivan PF, Magnusson PKE, van den Oord EJCG, Swedish Schizophrenia Consortium MBD-seq as a cost-effective approach for methylome-wide association studies:demonstration in 1500 case-control samples. Epigenomics 2012, 4:605-621. 10.2217/epi.12.59, 3923085, 23244307, Swedish Schizophrenia Consortium.
24. Clark C, Palta P, Joyce CJ, Scott C, Grundberg E, Deloukas P, Palotie A, Coffey AJ. A comparison of the whole genome approach of MeDIP-seq to the targeted approach of the Infinium HumanMethylation450 BeadChip ® for methylome profiling. PLoS ONE 2012, 7:e50233. 10.1371/journal.pone.0050233, 3510246, 23209683.
25. De Meyer T, Mampaey E, Vlemmix M, Denil S, Trooskens G, Renard JP, De Keulenaer S, Dehan P, Menschaert G, Van Criekinge W. Quality evaluation of methyl binding domain based kits for enrichment DNA-methylation sequencing. PLoS ONE 2013, 8:e59068. 10.1371/journal.pone.0059068, 3598902, 23554971.
26. Nair SS, Coolen MW, Stirzaker C, Song JZ, Statham AL, Strbenac D, Robinson MD, Clark SJ. Comparison of methyl-DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain (MBD) protein capture for genome-wide DNA methylation analysis reveal CpG sequence coverage bias. Epigenetics 2011, 6:34-44. 10.4161/epi.6.1.13313, 20818161.
27. Serre D, Lee BH, Ting AH. MBD-isolated genome sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome. Nucleic Acids Res 2010, 38:391-399. 10.1093/nar/gkp992, 2811030, 19906696.
28. Chavez L, Jozefczuk J, Grimm C, Dietrich J, Timmermann B, Lehrach H, Herwig R, Adjaye J. Computational analysis of genome-wide DNA methylation during the differentiation of human embryonic stem cells along the endodermal lineage. Genome Res 2010, 20:1441-1450. 10.1101/gr.110114.110, 2945193, 20802089.
29. Lan X, Adams C, Landers M, Dudas M, Krissinger D, Marnellos G, Bonneville R, Xu M, Wang J, Huang THM, Meredith G, Jin VX. High resolution detection and analysis of CpG dinucleotides methylation using MBD-seq technology. PLoS ONE 2011, 6:e22226. 10.1371/journal.pone.0022226, 3136941, 21779396.
30. Feber A, Wilson GA, Zhang L, Presneau N, Idowu B, Down TA, Rakyan VK, Noon LA, Lloyd AC, Stupka E, Schiza V, Teschendorff AE, Schroth GP, Flanagan A, Beck S. Comparative methylome analysis of benign and malignant peripheral nerve sheath tumors. Genome Res 2011, 21:515-524. 10.1101/gr.109678.110, 3065699, 21324880.
31. Stevens M, Cheng JB, Li D, Xie M, Hong C, Maire CL, Ligon KL, Hirst M, Marra MA, Costello JF, Wang T. Estimating absolute methylation levels at single-CpG resolution from methylation enrichment and restriction enzyme sequencing methods. Genome Res 2013, 23:1541-1553. 10.1101/gr.152231.112, 3759729, 23804401.
32. Bock C, Tomazou EM, Brinkman A, Müller F, Simmer F, Gu H, Jäger N, Gnirke A, Stunnenberg HG, Meissner A. Genome-wide mapping of DNA methylation:a quantitative technology comparison. Nature Biotechnology 2010, 28:1106-1114. 10.1038/nbt.1681, 3066564, 20852634.
33. Robinson MD, Strbenac D, Stirzaker C, Statham AL, Song JZ, Speed TP, Clark SJ. Copy-number-aware differential analysis of quantitative DNA sequencing data. Genome Res 2012, 22:2489-2496. 10.1101/gr.139055.112, 3514678, 22879430.
34. Fader PS, Hardie BGS. A note on modelling underreported Poisson counts. J Appl Stat 2000, 27:953-964.
35. Abramowitz M, Stegun IA. Handbook of Mathematical Functions with Formulas, Graphs and Mathematical Tables 1972, New York:Dover Publications.
36. Pelizzola M, Koga Y, Urban AE, Krauthammer M, Weissman S, Halaban R, Molinaro AM. MEDME:an experimental and analytical methodology for the estimation of DNA methylation levels based on microarray derived MeDIP-enrichment. Genome Res 2008, 18:1652-1659. 10.1101/gr.080721.108, 2556264, 18765822.
37. Robinson MD, Stirzaker C, Statham AL, Coolen MW, Song JZ, Nair SS, Strbenac D, Speed TP, Clark SJ. Evaluation of affinity-based genome-wide DNA methylation data:effects of CpG density, amplification bias, and copy number variation. Genome Res 2010, 20:1719-1729. 10.1101/gr.110601.110, 2989998, 21045081.
38. Schmittlein DC, Bemmaor AC, Morrison DG. Why does the NBD model work? Robustness in representing product purchases, brand purchases and imperfectly recorded purchases. Marketing Sci 1985, 4:255-266.
39. Winkelmann R. Markov chain Monte Carlo analysis of underreported count data with an application to worker absenteeism. Empirical Economics 1996, 21:575-587.
40. Lister R, Pelizzola M, Dowen RH, Hawkins RD, Hon G, Tonti-Filippini J, Nery JR, Lee L, Ye Z, Ngo QM, Edsall L, Antosiewicz-Bourget J, Stewart R, Ruotti V, Millar AH, Thomson JA, Ren B, Ecker JR. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 2009, 462:315-322. 10.1038/nature08514, 2857523, 19829295.
41. Houseman EA, Christensen BC, Karagas MR, Wrensch MR, Nelson HH, Wiemels JL, Zheng S, Wiencke JK, Kelsey KT, Marsit CJ. Copy number variation has little impact on bead-array-based measures of DNA methylation. Bioinformatics 2009, 25:1999-2005. 10.1093/bioinformatics/btp364, 2723008, 19542153.
42. Pickrell J, Gaffney D, Gilad Y, Pritchard J. False positive peaks in ChIP-seq and other sequencing-based functional assays caused by unannotated high copy number regions. Bioinformatics 2011, 27:2144-2146. 10.1093/bioinformatics/btr354, 3137225, 21690102.
43. DNA Methylation Technology Comparison, Supplementary Website. [http://www.broadinstitute.org/labs/meissner/mirror/papers/meth-benchmark/index.html].
44. Taiwo O, Wilson GA, Morris T, Seisenberger S, Reik W, Pearce D, Beck S, Butcher LM. Methylome analysis using MeDIP-seq with low DNA concentrations. Nature Protocols 2012, 7:617-636. 10.1038/nprot.2012.012, 22402632.
45. Carvalho RH, Haberle V, Hou J, van Gent T, Thongjuea S, van Ijcken W, Kockx C, Brouwer R, Rijkers E, Sieuwerts A, Foekens J, van Vroonhoven M, Aerts J, Grosveld F, Lenhard B, Philipsen S. Genome-wide DNA methylation profiling of non-small cell lung carcinomas. Epigenetics Chromatin 2012, 5:9. 10.1186/1756-8935-5-9, 3407794, 22726460.
46. Hansen KD, Irizarry RA, Wu Z. Removing technical variability in RNA-seq data using conditional quantile normalization. Biostatistics 2012, 13:204-216. 10.1093/biostatistics/kxr054, 3297825, 22285995.
47. Wu G, Yi N, Absher D, Zhi D. Statistical quantification of methylation levels by next-generation sequencing. PLoS ONE 2011, 6:e21034. 10.1371/journal.pone.0021034, 3115964, 21698242.
48. Rue H, Held L. Gaussian Markov Random Fields:Theory and Applications 2005, London:Chapman & Hall/CRC Press.
49. Gene Expression Omnibus. [http://www.ncbi.nlm.nih.gov/geo].
50. Statham AL, Strbenac D, Coolen MW, Stirzaker C, Clark SJ, Robinson MD. Repitools:an R package for the analysis of enrichment-based epigenomic data. Bioinformatics 2010, 26:1662-1663. 10.1093/bioinformatics/btq247, 2887051, 20457667.
51. Mapability of Reference Genome from ENCODE (window size 100mer), direct link to bigWig file. [http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeMapability/wgEncodeCrgMapabilityAlign100mer.bigWig].
52. Mapability of Reference Genome from ENCODE (window size 50mer), direct link to bigWig file. [http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeMapability/wgEncodeCrgMapabilityAlign50mer.bigWig].
53. Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, Irizarry RA. Minfi:a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA Methylation microarrays. Bioinformatics 2014, doi:10.1093/bioinformatics/btu049.
54. Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biology 2010, 11:R25. 10.1186/gb-2010-11-3-r25, 2864565, 20196867.
55. Greenman CD, Bignell G, Butler A, Edkins S, Hinton J, Beare D, Swamy S, Santarius T, Chen L, Widaa S, Futreal PA, Stratton MR. PICNIC:an algorithm to predict absolute allelic copy number variation with microarray cancer data. Biostatistics 2010, 11:164-175. 10.1093/biostatistics/kxp045, 2800165, 19837654.
56. Bayesian tool for methylation analysis (BATMAN) on Wikipedia, the free encyclopedia. [http://en.wikipedia.org/wiki/Bayesian_tool_for_methylation_analysis].
57. BayMeth:improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach. [http://imlspenticton.uzh.ch/robinson_lab/BayMeth/index.html].
58. BALM. [http://motif.bmi.ohio-state.edu/BALM].