Combinatorial epigenetic patterns as quantitative predictors of chromatin biology

BMC Genomics

Volumn 15, Issue 1, 2014, Pages

  Cieślik, Marcin ^a   Bekiranov, Stefan ^a  

^a UNIVERSITY OF VIRGINIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELL PROTEIN; PROTEIN POL2; UNCLASSIFIED DRUG;

ANALYTIC METHOD; ARTICLE; CELL DIFFERENTIATION; CHROMATIN ASSEMBLY AND DISASSEMBLY; COMBINATORIAL LIBRARY; EMBRYO; ENHANCER REGION; EPIGENETIC REPRESSION; GENE TARGETING; HUMAN; HUMAN CELL; INTERNET; MACHINE LEARNING; MOLECULAR BIOLOGY; NON NEGATIVE MATRIX FACTORIZATION; PLURIPOTENT STEM CELL; PROMOTER REGION; PROTEIN BINDING; QUANTITATIVE ANALYSIS; SIGNAL TRANSDUCTION; STATISTICAL ANALYSIS;

ALGORITHMS; AREA UNDER CURVE; CHROMATIN; CHROMATIN IMMUNOPRECIPITATION; EMBRYONIC STEM CELLS; EPIGENOMICS; HISTONES; HUMANS; INTERNET; PRINCIPAL COMPONENT ANALYSIS; PROMOTER REGIONS, GENETIC; PROTEIN BINDING; ROC CURVE; USER-COMPUTER INTERFACE;

EID: 84896708512     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-15-76     Document Type: Article

References (85)

1. Kharchenko PV, Alekseyenko AA, Schwartz YB, Minoda A, Riddle NC, Ernst J, Sabo PJ, Larschan E, Gorchakov AA, Gu T, Linder-Basso D, Plachetka A, Shanower G, Tolstorukov MY, Luquette LJ, Xi R, Jung YL, Park RW, Bishop EP, Canfield TK, Sandstrom R, Thurman RE, MacAlpine DM, Stamatoyannopoulos JA, Kellis M, Elgin SCR, Kuroda MI, Pirrotta V, Karpen GH, Park PJ. Comprehensive analysis of the chromatin landscape in Drosophila melanogaster. Nature 2011, 471(7339):480-485. [http://dx.doi.org/10.1038/nature09725], 10.1038/nature09725, 3109908, 21179089.
2. Mikkelsen TS, Ku M, Jaffe DB, Issac B, Lieberman E, Giannoukos G, Alvarez P, Brockman W, Kim TK, Koche RP, Lee W, Mendenhall E, O'Donovan A, Presser A, Russ C, Xie X, Meissner A, Wernig M, Jaenisch R, Nusbaum C, Lander ES, Bernstein BE. Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 2007, 448(7153):553-560. [PMID: 17603471 PMCID: 2921165], 10.1038/nature06008, 2921165, 17603471.
3. Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, Bernstein BE, Bickel P, Brown JB, Cayting P, Chen Y, DeSalvo G, Epstein C, Fisher-Aylor KI, Euskirchen G, Gerstein M, Gertz J, Hartemink AJ, Hoffman MM, Iyer VR, Jung YL, Karmakar S, Kellis M, Kharchenko PV, Li Q, Liu T, Liu XS, Ma L, Milosavljevic A, Myers RM, et al. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res 2012, 22(9):1813-1831. [http://genome.cshlp.org/content/22/9/1813], 10.1101/gr.136184.111, 3431496, 22955991.
4. Wilbanks EG, Facciotti MT. Evaluation of algorithm performance in ChIP-Seq peak detection. PLoS ONE 2010, 5(7):e11471. [http://dx.doi.org/10.1371/journal.pone.0011471], 10.1371/journal.pone.0011471, 2900203, 20628599.
5. Zang C, Schones DE, Zeng C, Cui K, Zhao K, Peng W. A clustering approach for identification of enriched domains from histone modification ChIP-Seq data. Bioinformatics 2009, 25(15):1952-1958. [PMID: 19505939], 10.1093/bioinformatics/btp340, 2732366, 19505939.
6. Song Q, Smith A. Identifying dispersed epigenomic domains from ChIP-Seq data. Bioinformatics 2011, 27(6):870. 10.1093/bioinformatics/btr030, 3051331, 21325299.
7. Hoang SA, Xu X, Bekiranov S. Quantification of histone modification ChIP-seq enrichment for data mining and machine learning applications. BMC Res Notes 2011, 4:288. [PMID: 21834981], 10.1186/1756-0500-4-288, 3170335, 21834981.
8. Xu H, Wei CL, Lin F, Sung WK. An HMM approach to genome-wide identification of differential histone modification sites from ChIP-seq data. Bioinformatics 2008, 24(20):2344-2349. [http://bioinformatics.oxfordjournals.org/content/24/20/2344.abstract], 10.1093/bioinformatics/btn402, 18667444.
9. Strahl BD, Allis CD. The language of covalent histone modifications. Nature 2000, 403(6765):41-45. [http://www.nature.com/nature/journal/v403/n6765/full/403041a0.html], 10.1038/47412, 10638745.
10. Wang Z, Zang C, Rosenfeld JA, Schones DE, Barski A, Cuddapah S, Cui K, Roh TY, Peng W, Zhang MQ, Zhao K. Combinatorial patterns of histone acetylations and methylations in the human genome. Nature Genet 2008, 40(7):897-903. [PMID: 18552846], 10.1038/ng.154, 2769248, 18552846.
11. Ye T, Krebs AR, Choukrallah MA, Keime C, Plewniak F, Davidson I, Tora L. seqMINER: an integrated ChIP-seq data interpretation platform. Nucleic Acids Res 2011, 39(6):e35-e35. [http://nar.oxfordjournals.org/content/39/6/e35], 10.1093/nar/gkq1287, 3064796, 21177645.
12. Liu Y, Han JDJ. Application of Bayesian networks on large-scale biological data. Front Biol 2010, 5(2):98-104. [http://link.springer.com/article/10.1007/s11515-010-0023-8].
13. Santoni FA. EMdeCODE: a novel algorithm capable of reading words of epigenetic code to predict enhancers and retroviral integration sites and to identify H3R2me1 as a distinctive mark of coding versus non-coding genes. Nucleic Acids Res 2013, 41(3):e48-e48. [http://nar.oxfordjournals.org/content/41/3/e48] [PMID: 23234700], 10.1093/nar/gks1214, 3561958, 23234700.
14. Ernst J, Kellis M. ChromHMM: automating chromatin-state discovery and characterization. Nature Methods 2012, 9(3):215-216. [http://www.nature.com/nmeth/journal/v9/n3/abs/nmeth.1906.html], 10.1038/nmeth.1906, 3577932, 22373907.
15. Hoffman MM, Buske OJ, Bilmes JA, Noble WS. Segway: simultaneous segmentation of multiple functional genomics data sets with heterogeneous patterns of missing data. 2011, [http://noble.gs.washington.edu/proj/segway/manuscript/temposegment.nips09.hoffman.pdf].
16. Hoffman MM, Buske OJ, Wang J, Weng Z, Bilmes JA, Noble WS. Unsupervised pattern discovery in human chromatin structure through genomic segmentation. Nature Methods 2012, 9(5):473-476. [http://www.nature.com/nmeth/journal/v9/n5/full/nmeth.1937.html], 10.1038/nmeth.1937, 3340533, 22426492.
17. Hon G, Ren B, Wang W. ChromaSig: a probabilistic approach to finding common chromatin signatures in the human genome. PLoS Comput Biol 2008, 4(10):e1000201. [http://dx.doi.org/10.1371/journal.pcbi.1000201], 10.1371/journal.pcbi.1000201, 2556089, 18927605.
18. Ucar D, Hu Q, Tan K. Combinatorial chromatin modification patterns in the human genome revealed by subspace clustering. Nucleic Acids Res 2011, 39(10):4063-4075. [http://nar.oxfordjournals.org/content/39/10/4063], 10.1093/nar/gkr016, 3105409, 21266477.
19. Ernst J, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, Epstein CB, Zhang X, Wang L, Issner R, Coyne M, Ku M, Durham T, Kellis M, Bernstein BE. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 2011, 473(7345):43-49. [http://www.nature.com/nature/journal/v473/n7345/full/nature09906.html], 10.1038/nature09906, 3088773, 21441907.
20. Chen Y, Jørgensen M, Kolde R, Zhao X, Parker B, Valen E, Wen J, Sandelin A. Prediction of RNA Polymerase II recruitment, elongation and stalling from histone modification data. BMC Genomics 2011, 12:544. [http://www.biomedcentral.com/1471-2164/12/544/abstract] [PMID: 22047616], 10.1186/1471-2164-12-544, 3228824, 22047616.
21. Xu X, Hoang S, Mayo MW, Bekiranov S. Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression. BMC Bioinformatics 2010, 11:396. [http://www.biomedcentral.com/1471-2105/11/396/abstract] [PMID: 20653935], 2928206, 20653935.
22. Karlić R, Chung HR, Lasserre J, Vlahoviček K, Vingron M. Histone modification levels are predictive for gene expression. Proc Natl Acad Sci 2010, 107(7):2926-2931. [http://www.pnas.org/content/107/7/2926], 10.1073/pnas.0909344107, 2814872, 20133639.
23. Nathans LL, Oswald FL, Nimon K. Interpreting multiple linear regression: a guidebook of variable importance. Pract Assessment, Res Eval 2012, 17(9):2. [http://pareonline.net/pdf/v17n9.pdf].
24. Chong IG, Jun CH. Performance of some variable selection methods when multicollinearity is present. Chemometrics Intell Lab Syst 2005, 78(1-2):103-112. [http://www.sciencedirect.com/science/article/pii/S0169743905000031].
25. Ernst J, Kellis M. Discovery and characterization of chromatin states for systematic annotation of the human genome. Nat Biotech 2010, 28(8):817-825. [http://dx.doi.org/10.1038/nbt.1662].
26. Ruthenburg AJ, Li H, Patel DJ, David Allis C. Multivalent engagement of chromatin modifications by linked binding modules. Nature Rev Mol Cell Biol 2007, 8(12):983-994. [http://www.nature.com/nrm/journal/v8/n12/full/nrm2298.html].
27. Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 2010, 38(4):576-589. [http://www.sciencedirect.com/science/article/pii/S1097276510003667], 10.1016/j.molcel.2010.05.004, 2898526, 20513432.
28. Bonn S, Zinzen RP, Girardot C, Gustafson EH, Perez-Gonzalez A, Delhomme N, Ghavi-Helm Y, Wilczyéski B, Riddell A, Furlong EEM. Tissue-specific analysis of chromatin state identifies temporal signatures of enhancer activity during embryonic development. Nature Genet 2012, 44(2):148-156. [http://www.nature.com/ng/journal/v44/n2/full/ng.1064.html], 10.1038/ng.1064, 22231485.
29. Lee DD, Seung HS. Learning the parts of objects by non-negative matrix factorization. Nature 1999, 401(6755):788-791. [http://www.nature.com/nature/journal/v401/n6755/abs/401788a0.html], 10.1038/44565, 10548103.
30. Brunet JP, Tamayo P, Golub TR, Mesirov JP. Metagenes and molecular pattern discovery using matrix factorization. Proc Natl Acad Sci 2004, 101(12):4164-4169. [http://www.pnas.org/content/101/12/4164] [PMID: 15016911], 10.1073/pnas.0308531101, 384712, 15016911.
31. Pascual-Montano A, Carmona-Saez P, Chagoyen M, Tirado F, Carazo JM, Pascual-Marqui RD. bioNMF: a versatile tool for non-negative matrix factorization in biology. BMC Bioinformatics 2006, 7:366. [http://www.biomedcentral.com/1471-2105/7/366/abstract] [PMID: 16875499], 10.1186/1471-2105-7-366, 1550731, 16875499.
32. Lin CJ. Projected gradient methods for nonnegative matrix factorization. Neural Comput 2007, 19(10):2756-2779. [http://dx.doi.org/10.1162/neco.2007.19.10.2756], 10.1162/neco.2007.19.10.2756, 17716011.
33. Boutsidis C, Gallopoulos E. SVD based initialization: A head start for nonnegative matrix factorization. Pattern Recognit 2008, 41(4):1350-1362. [http://www.sciencedirect.com/science/article/pii/S0031320307004359].
34. Hoyer PO. Non-negative matrix factorization with sparseness constraints. J Mach Learn Res 2004, 5:1457-1469. [http://dl.acm.org/citation.cfm?id=10053321044709].
35. Devarajan K. Nonnegative matrix factorization: an analytical and interpretive tool in computational biology. PLoS Comput Biol 2008, 4(7):e1000029. [http://dx.doi.org/10.1371/journal.pcbi.1000029], 10.1371/journal.pcbi.1000029, 2447881, 18654623.
36. Jain A, Nandakumar K, Ross A. Score normalization in multimodal biometric systems. Pattern Recognit 2005, 38(12):2270-2285. [http://www.sciencedirect.com/science/article/pii/S0031320305000592].
37. Okun O, Priisalu H. Nonnegative matrix factorization for pattern recognition. Pattern Recognition 2005, ACTA Press, [http://www.actapress.com/Abstract.aspx?paperId=21730].
38. Wong MM, Cox LK, Chrivia JC. The chromatin remodeling protein, SRCAP, is critical for deposition of the histone variant H2A.Z at promoters. J Biol Chem 2007, 282(36):26132-26139. [http://www.jbc.org/content/282/36/26132] [PMID: 17617668], 10.1074/jbc.M703418200, 17617668.
39. Calo E, Wysocka J. Modification of enhancer chromatin: what, how, and why?. Mol Cell 2013, 49(5):825-837. [http://www.sciencedirect.com/science/article/pii/S1097276513001020], 10.1016/j.molcel.2013.01.038, 23473601.
40. Bannister AJ, Kouzarides T. Regulation of chromatin by histone modifications. Cell Res 2011, 21(3):381-395. [http://www.nature.com/cr/journal/v21/n3/full/cr201122a.html], 10.1038/cr.2011.22, 3193420, 21321607.
41. Papp B, Plath K. Reprogramming to pluripotency: stepwise resetting of the epigenetic landscape. Cell Res 2011, 21(3):486-501. [http://www.nature.com/cr/journal/v21/n3/abs/cr201128a.html], 10.1038/cr.2011.28, 3193418, 21321600.
42. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol 2010, 11(10):R106. [http://genomebiology.com/2010/11/10/R106], 10.1186/gb-2010-11-10-r106, 3218662, 20979621.
43. Lieber M, Smith B, Szakal A, Nelson-Rees W, Todaro G. A continuous tumor-cell line from a human lung carcinoma with properties of type II alveolar epithelial cells. Int J Cancer. Journal International Du Cancer 1976, 17:62-70. [http://www.ncbi.nlm.nih.gov/pubmed/175022] [PMID: 175022].
44. Liokatis S, Stützer A, Elsüsser SJ, Theillet FX, Klingberg R, van Rossum B, Schwarzer D, Allis CD, Fischle W, Selenko P. Phosphorylation of histone H3 Ser10 establishes a hierarchy for subsequent intramolecular modification events. Nature Struct Mol Biol 2012, 19(8):819-823. [http://www.nature.com/nsmb/journal/v19/n8/full/nsmb.2310.html].
45. Guccione E, Martinato F, Finocchiaro G, Luzi L, Tizzoni L, Dall' Olio V, Zardo G, Nervi C, Bernard L, Amati B. Myc-binding-site recognition in the human genome is determined by chromatin context. Nature Cell Biol 2006, 8(7):764-770. [http://www.nature.com/ncb/journal/v8/n7/full/ncb1434.html], 10.1038/ncb1434, 16767079.
46. Schuster-Böckler B, Lehner B. Chromatin organization is a major influence on regional mutation rates in human cancer cells. Nature 2012, [http://www.nature.com/nature/journal/vaop/ncurrent/abs/nature11273.html].
47. Kiang MY. A comparative assessment of classification methods. Decis Support Syst 2003, 35(4):441-454. [http://www.sciencedirect.com/science/article/pii/S0167923602001100].
48. Park MY, Hastie T. Penalized logistic regression for detecting gene interactions. Biostatistics 2008, 9:30-50. [http://biostatistics.oxfordjournals.org/content/9/1/30] [PMID: 17429103], 10.1093/biostatistics/kxm010, 17429103.
49. Farrar DE, Glauber RR. Multicollinearity in regression analysis: the problem revisited. Rev Econ Stat 1967, 49:92-107. [http://www.jstor.org/stable/1937887] [ArticleType: research-article/Full publication date: Feb., 1967/Copyright©1967 The MIT Press].
50. Ward JH. Hierarchical grouping to optimize an objective function. J Am Stat Assoc 1963, 58(301):236-244. [http://www.tandfonline.com/doi/abs/10.1080/01621459.1963.10500845].
51. Cosine similarity. 2013, [http://en.wikipedia.org/w/index.php?title=Cosine_similarity&oldid=572823419] [Page Version ID: 572823419].
52. Munkres J. Algorithms for the assignment and transportation problems. J Soc Ind Appl Math 1957, 5:32-38. [http://www.jstor.org/stable/2098689] [ArticleType: research-article/Full publication date: Mar., 1957/Copyright©1957 Society for Industrial and Applied Mathematics].
53. Dong X, Greven MC, Kundaje A, Djebali S, Brown JB, Cheng C, Gingeras TR, Gerstein M, Guigó R, Birney E, Weng Z. Modeling gene expression using chromatin features in various cellular contexts. Genome Biology 2012, 13(9):R53. [http://genomebiology.com/2012/13/9/R53/abstract] [PMID: 22950368], 10.1186/gb-2012-13-9-r53, 3491397, 22950368.
54. Guenther MG, Levine SS, Boyer LA, Jaenisch R, Young RA. A chromatin landmark and transcription initiation at most promoters in human cells. Cell 2007, 130:77-88. [http://www.sciencedirect.com/science/article/pii/S0092867407006812], 10.1016/j.cell.2007.05.042, 3200295, 17632057.
55. De Santa F, Barozzi I, Mietton F, Ghisletti S, Polletti S, Tusi BK, Muller H, Ragoussis J, Wei CL, Natoli G. A large fraction of extragenic RNA pol II transcription sites overlap enhancers. PLoS Biol 2010, 8(5):e1000384. [http://dx.doi.org/10.1371/journal.pbio.1000384], 10.1371/journal.pbio.1000384, 2867938, 20485488.
56. Rada-Iglesias A, Bajpai R, Swigut T, Brugmann SA, Flynn RA, Wysocka J. A unique chromatin signature uncovers early developmental enhancers in humans. Nature 2011, 470(7333):279-283. [http://www.nature.com/nature/journal/v470/n7333/abs/nature09692.html], 10.1038/nature09692, 21160473.
57. Pekowska A, Benoukraf T, Zacarias-Cabeza J, Belhocine M, Koch F, Holota H, Imbert J, Andrau JC, Ferrier P, Spicuglia S. H3K4 tri-methylation provides an epigenetic signature of active enhancers. EMBO J 2011, 30(20):4198-4210. [http://www.nature.com/emboj/journal/v30/n20/full/emboj2011295a.html], 10.1038/emboj.2011.295, 3199384, 21847099.
58. Bargaje R, Alam MP, Patowary A, Sarkar M, Ali T, Gupta S, Garg M, Singh M, Purkanti R, Scaria V, Sivasubbu S, Brahmachari V, Pillai B. Proximity of H2A.Z containing nucleosome to the transcription start site influences gene expression levels in the mammalian liver and brain. Nucleic Acids Res 2012, 40(18):8965-8978. [http://nar.oxfordjournals.org/content/40/18/8965], 10.1093/nar/gks665, 3467062, 22821566.
59. Hu G, Cui K, Northrup D, Liu C, Wang C, Tang Q, Ge K, Levens D, Crane-Robinson C, Zhao K. H2A.Z facilitates access of active and repressive complexes to chromatin in embryonic stem cell self-renewal and differentiation. Cell Stem Cell 2013, 12(2):180-192. [http://www.sciencedirect.com/science/article/pii/S1934590912006376], 10.1016/j.stem.2012.11.003, 3570599, 23260488.
60. Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, Sivachenko A, Zhang X, Bernstein BE, Nusbaum C, Jaffe DB, Gnirke A, Jaenisch R, Lander ES. Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 2008, 454(7205):766-770. [http://www.ncbi.nlm.nih.gov/pubmed/18600261] [PMID: 18600261], 2896277, 18600261.
61. Wang Y, Zhang XS, Xia Y. Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data. Nucleic Acids Res 2009, 37(18):5943-5958. [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2764433/] [PMID: 19661283 PMCID: PMC2764433], 10.1093/nar/gkp625, 2764433, 19661283.
62. Hon GC, Hawkins RD, Ren B. Predictive chromatin signatures in the mammalian genome. Human Mol Genet 2009, 18(R2):R195-R201. [http://hmg.oxfordjournals.org/content/18/R2/R195.abstract].
63. Asp P, Blum R, Vethantham V, Parisi F, Micsinai M, Cheng J, Bowman C, Kluger Y, Dynlacht BD. Genome-wide remodeling of the epigenetic landscape during myogenic differentiation. Proc Natl Acad Sci 2011, 108(22):E149-E158. [http://www.pnas.org/content/108/22/E149] [PMID: 21551099], 10.1073/pnas.1102223108, 3107312, 21551099.
64. Liberzon A, Subramanian A, Pinchback R, Thorvaldsdóttir H, Tamayo P, Mesirov JP. Molecular signatures database (MSigDB) 3.0. Bioinformatics 2011, 27(12):1739-1740. [http://bioinformatics.oxfordjournals.org/content/27/12/1739], 10.1093/bioinformatics/btr260, 3106198, 21546393.
65. Newton MA, Quintana FA, Boon J, Sengupta S, Ahlquist P. Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis. Ann Appl Stat 2007, 1:85-106. [http://www.jstor.org/stable/4537423] [ArticleType: research-article/Full publication date: Jun., 2007/Copyright©2007 Institute of Mathematical Statistics].
66. Subramanian A, Kuehn H, Gould J, Tamayo P, Mesirov JP. GSEA-P: a desktop application for gene set enrichment analysis. Bioinformatics 2007, 23(23):3251-3253. [http://bioinformatics.oxfordjournals.org/content/23/23/3251] [PMID: 17644558], 10.1093/bioinformatics/btm369, 17644558.
67. Moran JL, Li Y, Hill AA, Mounts WM, Miller CP. Gene expression changes during mouse skeletal myoblast differentiation revealed by transcriptional profiling. Physiolo Genomics 2002, 10(2):103-111. [http://physiolgenomics.physiology.org/content/10/2/103] [PMID: 12181367].
68. Jean-Baptiste G, Yang Z, Khoury C, Gaudio S, Greenwood MT. Peptide and non-peptide G-protein coupled receptors (GPCRs) in skeletal muscle. Peptides 2005, 26(8):1528-1536. [http://www.sciencedirect.com/science/article/pii/S0196978105001245], 10.1016/j.peptides.2005.03.011, 16042993.
69. Rayman JB, Takahashi Y, Indjeian VB, Dannenberg JH, Catchpole S, Watson RJ, te Riele H, Dynlacht BD. E2F mediates cell cycle-dependent transcriptional repression in vivo by recruitment of an HDAC1/mSin3B corepressor complex. Genes Dev 2002, 16(8):933-947. [http://genesdev.cshlp.org/content/16/8/933] [PMID: 11959842], 10.1101/gad.969202, 152357, 11959842.
70. Kennedy PJ, Feng J, Robison AJ, Maze I, Badimon A, Mouzon E, Chaudhury D, Damez-Werno DM, Haggarty SJ, Han MH, Bassel-Duby R, Olson EN, Nestler EJ. Class I HDAC inhibition blocks cocaine-induced plasticity by targeted changes in histone methylation. Nature Neurosci 2013, 16(4):434-440. [http://www.nature.com/neuro/journal/v16/n4/full/nn.3354.html], 10.1038/nn.3354, 3609040, 23475113.
71. Lang KC, Lin IH, Teng HF, Huang YC, Li CL, Tang KT, Chen SL. Simultaneous overexpression of Oct4 and Nanog abrogates terminal myogenesis. Am J Physiol - Cell Physiol 2009, 297:C43-C54. [http://ajpcell.physiology.org/content/297/1/C43] [PMID: 19403798], 10.1152/ajpcell.00468.2008, 19403798.
72. Tan KY, Eminli S, Hettmer S, Hochedlinger K, Wagers AJ. Efficient generation of iPS cells from skeletal muscle stem cells. PLoS ONE 2011, 6(10):e26406. [http://dx.doi.org/10.1371/journal.pone.0026406], 10.1371/journal.pone.0026406, 3196574, 22028872.
73. Müller FJ, Laurent LC, Kostka D, Ulitsky I, Williams R, Lu C, Park IH, Rao MS, Shamir R, Schwartz PH, Schmidt NO, Loring JF. Regulatory networks define phenotypic classes of human stem cell lines. Nature 2008, 455(7211):401-405. [http://www.nature.com/nature/journal/v455/n7211/full/nature07213.html], 10.1038/nature07213, 2637443, 18724358.
74. Wong DJ, Liu H, Ridky TW, Cassarino D, Segal E, Chang HY. Module map of stem cell genes guides creation of epithelial cancer stem cells. Cell Stem Cell 2008, 2(4):333-344. [http://www.sciencedirect.com/science/article/pii/S1934590908000738], 10.1016/j.stem.2008.02.009, 2628721, 18397753.
75. Guillamet D, Vitrià J, Schiele B. Introducing a weighted non-negative matrix factorization for image classification. Pattern Recognit Lett 2003, 24(14):2447-2454. [http://www.sciencedirect.com/science/article/pii/S0167865503000898].
76. Li SZ, Hou X, Zhang H, Cheng Q. Learning spatially localized, parts-based representation. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001, Volume 1 2001:I-207-I-212 vol.1. doi:10.1109/CVPR.2001.990477.
77. Orkin S, Hochedlinger K. Chromatin connections to pluripotency and cellular reprogramming. Cell 2011, 145(6):835-850. [http://www.sciencedirect.com/science/article/pii/S0092867411005769], 10.1016/j.cell.2011.05.019, 21663790.
78. van der Walt S, Colbert S, Varoquaux G. The NumPy array: a structure for efficient numerical computation. Comput Sci Eng 2011, 13(2):22-30.
79. Jones E, Oliphant T, Peterson P. SciPy: Open source scientific tools for Python. 2001, [http://www.scipy.org/Citing_SciPy].
80. Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay E. Scikit-learn: machine learning in Python. J Mach Learn Res 2011, 12:2825-2830. [http://dl.acm.org/citation.cfm?id=19530482078195].
81. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 2010, 26(6):841-842. [http://bioinformatics.oxfordjournals.org/content/26/6/841] [PMID: 20110278], 10.1093/bioinformatics/btq033, 2832824, 20110278.
82. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The sequence alignment/map format and SAMtools. Bioinformatics 2009, 25(16):2078-2079. [http://bioinformatics.oxfordjournals.org/content/25/16/2078] [PMID: 19505943], 10.1093/bioinformatics/btp352, 2723002, 19505943.
83. Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M, Kokocinski F, Aken BL, Barrell D, Zadissa A, Searle S, Barnes I, Bignell A, Boychenko V, Hunt T, Kay M, Mukherjee G, Rajan J, Despacio-Reyes G, Saunders G, Steward C, Harte R, Lin M, Howald C, Tanzer A, Derrien T, Chrast J, Walters N, Balasubramanian S, Pei B, Tress M, et al. GENCODE: The reference human genome annotation for The ENCODE Project. Genome Res 2012, 22(9):1760-1774. [http://genome.cshlp.org/content/22/9/1760], 10.1101/gr.135350.111, 3431492, 22955987.
84. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Stat Soc. Ser B (Methodological) 1995, 57:289-300. [http://www.jstor.org/stable/2346101] [ArticleType: research-article/Full publication date: 1995/Copyright©1995 Royal Statistical Society].
85. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods 2012, 9(4):357-359. [http://www.nature.com/nmeth/journal/v9/n4/abs/nmeth.1923.html], 10.1038/nmeth.1923, 3322381, 22388286.