Haslam DW, James WP. Obesity. Lancet. 2005;366:1197–209.
Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX, et al. Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss: an update of the 1997 American Heart Association Scientific Statement on Obesity and Heart Disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation. 2006;113:898–918.
Rodgers A, Ezzati M, Vander Hoorn S, Lopez AD, Lin RB, Murray CJ. Distribution of major health risks: findings from the Global Burden of Disease study. PLoS Med. 2004;1:e27.
Sturm R. The effects of obesity, smoking, and drinking on medical problems and costs. Health Aff (Millwood). 2002;21:245–53.
Scherer PE. Adipose tissue: from lipid storage compartment to endocrine organ. Diabetes. 2006;55:1537–45.
Hajer GR, van Haeften TW, Visseren FL. Adipose tissue dysfunction in obesity, diabetes, and vascular diseases. Eur Heart J. 2008;29:2959–71.
Wajchenberg BL. Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. Endocr Rev. 2000;21:697–738.
Wajchenberg BL, Giannella-Neto D, da Silva ME, Santos RF. Depot-specific hormonal characteristics of subcutaneous and visceral adipose tissue and their relation to the metabolic syndrome. Horm Metab Res. 2002;34:616–21.
Jensen MD. Role of body fat distribution and the metabolic complications of obesity. J Clin Endocrinol Metab. 2008;93:S57–63.
Manolopoulos KN, Karpe F, Frayn KN. Gluteofemoral body fat as a determinant of metabolic health. Int J Obes (Lond). 2010;34:949–59.
Snijder MB, Visser M, Dekker JM, Goodpaster BH, Harris TB, Kritchevsky SB, et al. Low subcutaneous thigh fat is a risk factor for unfavourable glucose and lipid levels, independently of high abdominal fat. The Health ABC Study. Diabetologia. 2005;48:301–8.
Bluher M. The distinction of metabolically ‘healthy’ from ‘unhealthy’ obese individuals. Curr Opin Lipidol. 2010;21:38–43.
Canoy D, Boekholdt SM, Wareham N, Luben R, Welch A, Bingham S, et al. Body fat distribution and risk of coronary heart disease in men and women in the European Prospective Investigation Into Cancer and Nutrition in Norfolk cohort: a population-based prospective study. Circulation. 2007;116:2933–43.
Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P, et al. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case–control study. Lancet. 2005;366:1640–9.
McCarthy MI. Genomics, type 2 diabetes, and obesity. N Engl J Med. 2010;363:2339–50.
Visscher PM, Brown MA, McCarthy MI, Yang J. Five years of GWAS discovery. Am J Hum Genet. 2012;90:7–24.
Franks PW, Ling C. Epigenetics and obesity: the devil is in the details. BMC Med. 2010;8:88.
Pinnick KE, Karpe F. DNA methylation of genes in adipose tissue. Proc Nutr Soc. 2011;70:57–63.
Dabelea D, Crume T. Maternal environment and the transgenerational cycle of obesity and diabetes. Diabetes. 2011;60:1849–55.
Heijmans BT, Tobi EW, Stein AD, Putter H, Blauw GJ, Susser ES, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc Natl Acad Sci U S A. 2008;105:17046–9.
Jirtle RL, Skinner MK. Environmental epigenomics and disease susceptibility. Nat Rev Genet. 2007;8:253–62.
Lumey LH, Stein AD, Kahn HS, van der Pal-de Bruin KM, Blauw GJ, Zybert PA, et al. Cohort profile: the Dutch Hunger Winter families study. Int J Epidemiol. 2007;36:1196–204.
Tobi EW, Lumey LH, Talens RP, Kremer D, Putter H, Stein AD, et al. DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific. Hum Mol Genet. 2009;18:4046–53.
Godfrey KM, Sheppard A, Gluckman PD, Lillycrop KA, Burdge GC, McLean C, et al. Epigenetic gene promoter methylation at birth is associated with child’s later adiposity. Diabetes. 2011;60:1528–34.
Feinberg AP, Irizarry RA, Fradin D, Aryee MJ, Murakami P, Aspelund T, et al. Personalized epigenomic signatures that are stable over time and covary with body mass index. Sci Transl Med. 2010;2:49ra67.
Wang X, Zhu H, Snieder H, Su S, Munn D, Harshfield G, et al. Obesity related methylation changes in DNA of peripheral blood leukocytes. BMC Med. 2010;8:87.
Xu X, Su S, Barnes VA, De Miguel C, Pollock J, Ownby D, Shi H, Zhu H, Snieder H, Wang X: A genome-wide methylation study on obesity: Differential variability and differential methylation. Epigenetics. 2013;8:522–33.
Almen MS, Jacobsson JA, Moschonis G, Benedict C, Chrousos GP, Fredriksson R, et al. Genome wide analysis reveals association of a FTO gene variant with epigenetic changes. Genomics. 2012;99:132–7.
Milagro FI, Campion J, Cordero P, Goyenechea E, Gomez-Uriz AM, Abete I, et al. A dual epigenomic approach for the search of obesity biomarkers: DNA methylation in relation to diet-induced weight loss. FASEB J. 2011;25:1378–89.
Moleres A, Campion J, Milagro FI, Marcos A, Campoy C, Garagorri JM, et al. Differential DNA methylation patterns between high and low responders to a weight loss intervention in overweight or obese adolescents: the EVASYON study. FASEB J. 2013;27:2504–12.
Toperoff G, Aran D, Kark JD, Rosenberg M, Dubnikov T, Nissan B, et al. Genome-wide survey reveals predisposing diabetes type 2-related DNA methylation variations in human peripheral blood. Hum Mol Genet. 2012;21:371–83.
Hidalgo B, Irvin MR, Sha J, Zhi D, Aslibekyan S, Absher D, et al. Epigenome-wide association study of fasting measures of glucose, insulin, and HOMA-IR in the Genetics of Lipid Lowering Drugs and Diet Network study. Diabetes. 2014;63:801–7.
Melzner I, Scott V, Dorsch K, Fischer P, Wabitsch M, Bruderlein S, et al. Leptin gene expression in human preadipocytes is switched on by maturation-induced demethylation of distinct CpGs in its proximal promoter. J Biol Chem. 2002;277:45420–7.
Yokomori N, Tawata M, Onaya T. DNA demethylation during the differentiation of 3T3-L1 cells affects the expression of the mouse GLUT4 gene. Diabetes. 1999;48:685–90.
Noer A, Boquest AC, Collas P. Dynamics of adipogenic promoter DNA methylation during clonal culture of human adipose stem cells to senescence. BMC Cell Biol. 2007;8:18.
Cordero P, Campion J, Milagro FI, Goyenechea E, Steemburgo T, Javierre BM, et al. Leptin and TNF-alpha promoter methylation levels measured by MSP could predict the response to a low-calorie diet. J Physiol Biochem. 2011;67:463–70.
Bouchard L, Rabasa-Lhoret R, Faraj M, Lavoie ME, Mill J, Perusse L, et al. Differential epigenomic and transcriptomic responses in subcutaneous adipose tissue between low and high responders to caloric restriction. Am J Clin Nutr. 2010;91:309–20.
Grundberg E, Meduri E, Sandling JK, Hedman AK, Keildson S, Buil A, et al. Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements. Am J Hum Genet. 2013;93:876–90.
Ribel-Madsen R, Fraga MF, Jacobsen S, Bork-Jensen J, Lara E, Calvanese V, et al. Genome-wide analysis of DNA methylation differences in muscle and fat from monozygotic twins discordant for type 2 diabetes. PLoS One. 2012;7:e51302.
Ronn T, Volkov P, Davegardh C, Dayeh T, Hall E, Olsson AH, et al. A six months exercise intervention influences the genome-wide DNA methylation pattern in human adipose tissue. PLoS Genet. 2013;9:e1003572.
Slieker RC, Bos SD, Goeman JJ, Bovee JV, Talens RP, van der Breggen R, et al. Identification and systematic annotation of tissue-specific differentially methylated regions using the Illumina 450k array. Epigenetics Chromatin. 2013;6:26.
Keller M, Kralisch S, Rohde K, Schleinitz D, Dietrich A, Schon MR, et al. Global DNA methylation levels in human adipose tissue are related to fat distribution and glucose homeostasis. Diabetologia. 2014;57:2374–83.
Buchwald H, Estok R, Fahrbach K, Banel D, Jensen MD, Pories WJ, et al. Weight and type 2 diabetes after bariatric surgery: systematic review and meta-analysis. Am J Med. 2009;122:248–256 e245.
White S, Brooks E, Jurikova L, Stubbs RS. Long-term outcomes after gastric bypass. Obes Surg. 2005;15:155–63.
Barres R, Kirchner H, Rasmussen M, Yan J, Kantor FR, Krook A, et al. Weight loss after gastric bypass surgery in human obesity remodels promoter methylation. Cell Rep. 2013;3:1020–7.
Ahrens M, Ammerpohl O, von Schonfels W, Kolarova J, Bens S, Itzel T, et al. DNA methylation analysis in nonalcoholic fatty liver disease suggests distinct disease-specific and remodeling signatures after bariatric surgery. Cell Metab. 2013;18:296–302.
Dunn OJ. Multiple comparisons among means. J Am Stat Assoc. 1961;56:52–64.
Morris TJ, Butcher LM, Feber A, Teschendorff AE, Chakravarthy AR, Wojdacz TK, et al. ChAMP: 450k chip analysis methylation pipeline. Bioinformatics. 2014;30:428–30.
A Catalog of Published Genome-Wide Association Studies. Available at: www.genome.gov/gwastudies.
Below JE, Gamazon ER, Morrison JV, Konkashbaev A, Pluzhnikov A, McKeigue PM, et al. Genome-wide association and meta-analysis in populations from Starr County, Texas, and Mexico City identify type 2 diabetes susceptibility loci and enrichment for expression quantitative trait loci in top signals. Diabetologia. 2011;54:2047–55.
Boguslavsky S, Chiu T, Foley KP, Osorio-Fuentealba C, Antonescu CN, Bayer KU, et al. Myo1c binding to submembrane actin mediates insulin-induced tethering of GLUT4 vesicles. Mol Biol Cell. 2012;23:4065–78.
Bose A, Guilherme A, Robida SI, Nicoloro SM, Zhou QL, Jiang ZY, et al. Glucose transporter recycling in response to insulin is facilitated by myosin Myo1c. Nature. 2002;420:821–4.
Bose A, Robida S, Furcinitti PS, Chawla A, Fogarty K, Corvera S, et al. Unconventional myosin Myo1c promotes membrane fusion in a regulated exocytic pathway. Mol Cell Biol. 2004;24:5447–58.
Choi YH, Park S, Hockman S, Zmuda-Trzebiatowska E, Svennelid F, Haluzik M, et al. Alterations in regulation of energy homeostasis in cyclic nucleotide phosphodiesterase 3B-null mice. J Clin Invest. 2006;116:3240–51.
Deram S, Nicolau CY, Perez-Martinez P, Guazzelli I, Halpern A, Wajchenberg BL, et al. Effects of perilipin (PLIN) gene variation on metabolic syndrome risk and weight loss in obese children and adolescents. J Clin Endocrinol Metab. 2008;93:4933–40.
Huang J, Imamura T, Babendure JL, Lu JC, Olefsky JM. Disruption of microtubules ablates the specificity of insulin signaling to GLUT4 translocation in 3T3-L1 adipocytes. J Biol Chem. 2005;280:42300–6.
Perez-Martinez P, Yiannakouris N, Lopez-Miranda J, Arnett D, Tsai M, Galan E, et al. Postprandial triacylglycerol metabolism is modified by the presence of genetic variation at the perilipin (PLIN) locus in 2 white populations. Am J Clin Nutr. 2008;87:744–52.
Qi L, Corella D, Sorli JV, Portoles O, Shen H, Coltell O, et al. Genetic variation at the perilipin (PLIN) locus is associated with obesity-related phenotypes in White women. Clin Genet. 2004;66:299–310.
Richardson K, Louie-Gao Q, Arnett DK, Parnell LD, Lai CQ, Davalos A, et al. The PLIN4 variant rs8887 modulates obesity related phenotypes in humans through creation of a novel miR-522 seed site. PLoS One. 2011;6:e17944.
Soenen S, Mariman EC, Vogels N, Bouwman FG, den Hoed M, Brown L, et al. Relationship between perilipin gene polymorphisms and body weight and body composition during weight loss and weight maintenance. Physiol Behav. 2009;96:723–8.
Yip MF, Ramm G, Larance M, Hoehn KL, Wagner MC, Guilhaus M, et al. CaMKII-mediated phosphorylation of the myosin motor Myo1c is required for insulin-stimulated GLUT4 translocation in adipocytes. Cell Metab. 2008;8:384–98.
Zmuda-Trzebiatowska E, Oknianska A, Manganiello V, Degerman E. Role of PDE3B in insulin-induced glucose uptake, GLUT-4 translocation and lipogenesis in primary rat adipocytes. Cell Signal. 2006;18:382–90.
Procino A, Cillo C. The HOX genes network in metabolic diseases. Cell Biol Int. 2013;37:1145–8.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a pratical and powerful approach to multiple testing. J Royal Stat Soc B. 1995;57:289–300.
Bird A. DNA methylation patterns and epigenetic memory. Genes Dev. 2002;16:6–21.
Capel F, Viguerie N, Vega N, Dejean S, Arner P, Klimcakova E, et al. Contribution of energy restriction and macronutrient composition to changes in adipose tissue gene expression during dietary weight-loss programs in obese women. J Clin Endocrinol Metab. 2008;93:4315–22.
Clement K, Viguerie N, Poitou C, Carette C, Pelloux V, Curat CA, et al. Weight loss regulates inflammation-related genes in white adipose tissue of obese subjects. FASEB J. 2004;18:1657–69.
Franck N, Gummesson A, Jernas M, Glad C, Svensson PA, Guillot G, et al. Identification of adipocyte genes regulated by caloric intake. J Clin Endocrinol Metab. 2011;96:E413–8.
Johansson LE, Danielsson AP, Parikh H, Klintenberg M, Norstrom F, Groop L, et al. Differential gene expression in adipose tissue from obese human subjects during weight loss and weight maintenance. Am J Clin Nutr. 2012;96:196–207.
Adalsteinsson BT, Gudnason H, Aspelund T, Harris TB, Launer LJ, Eiriksdottir G, et al. Heterogeneity in white blood cells has potential to confound DNA methylation measurements. PLoS One. 2012;7:e46705.
Wu H, Zhang Y. Reversing DNA methylation: mechanisms, genomics, and biological functions. Cell. 2014;156:45–68.
Kaelin Jr WG, McKnight SL. Influence of metabolism on epigenetics and disease. Cell. 2013;153:56–69.
Rosen ED, Spiegelman BM. What we talk about when we talk about fat. Cell. 2014;156:20–44.
Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012;13:86.
Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 2014;15:R31.
Houseman EA, Molitor J, Marsit CJ. Reference-free cell mixture adjustments in analysis of DNA methylation data. Bioinformatics. 2014;30:1431–9.
Chen W, Chang B, Wu X, Li L, Sleeman M, Chan L. Inactivation of Plin4 downregulates Plin5 and reduces cardiac lipid accumulation in mice. Am J Physiol Endocrinol Metab. 2013;304:E770–9.
Turcot V, Bouchard L, Faucher G, Tchernof A, Deshaies Y, Perusse L, et al. DPP4 gene DNA methylation in the omentum is associated with its gene expression and plasma lipid profile in severe obesity. Obesity (Silver Spring). 2011;19:388–95.
Drucker DJ. The biology of incretin hormones. Cell Metab. 2006;3:153–65.
Lambeir AM, Durinx C, Scharpe S, De Meester I. Dipeptidyl-peptidase IV from bench to bedside: an update on structural properties, functions, and clinical aspects of the enzyme DPP IV. Crit Rev Clin Lab Sci. 2003;40:209–94.
Campbell CS, Caperuto LC, Hirata AE, Araujo EP, Velloso LA, Saad MJ, et al. The phosphatidylinositol/AKT/atypical PKC pathway is involved in the improved insulin sensitivity by DHEA in muscle and liver of rats in vivo. Life Sci. 2004;76:57–70.
Fruhbeck G, Becerril S, Sainz N, Garrastachu P, Garcia-Velloso MJ. BAT: a new target for human obesity? Trends Pharmacol Sci. 2009;30:387–96.
Glessner JT, Bradfield JP, Wang K, Takahashi N, Zhang H, Sleiman PM, et al. A genome-wide study reveals copy number variants exclusive to childhood obesity cases. Am J Hum Genet. 2010;87:661–6.
Morton NM, Nelson YB, Michailidou Z, Di Rollo EM, Ramage L, Hadoke PW, et al. A stratified transcriptomics analysis of polygenic fat and lean mouse adipose tissues identifies novel candidate obesity genes. PLoS One. 2011;6:e23944.
Silverstein RL, Febbraio M. CD36, a scavenger receptor involved in immunity, metabolism, angiogenesis, and behavior. Sci Signal. 2009;2:re3.
Sun HX, Du WN, Li YF, Zuo J, Wu GD, Shen Y, et al. Linkage disequilibrium analysis of the single nucleotide polymorphisms in the PRKCZ gene. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2002;24:474–80.
Sun HX, Du WN, Li YF, Zuo J, Wu GD, Shen Y, et al. Functional analysis of the single nucleotide polymorphisms in the PRKCZ gene. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2002;24:471–3.
Sun HX, Du WN, Zuo J, Wu GD, Shi GB, Shen Y, et al. The association of two single nucleotide polymorphisms in PRKCZ and UTS2 respectively with type 2 diabetes in Han people of northern China. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2002;24:223–7.
Vernochet C, McDonald ME, Farmer SR. Brown adipose tissue: a promising target to combat obesity. Drug News Perspect. 2010;23:409–17.
Ravussin E, Kozak LP. Have we entered the brown adipose tissue renaissance? Obes Rev. 2009;10:265–8.
Cohen DE. New players on the metabolic stage: how do you like them Acots? Adipocyte. 2013;2:3–6.
Zhang Y, Li Y, Niepel MW, Kawano Y, Han S, Liu S, et al. Targeted deletion of thioesterase superfamily member 1 promotes energy expenditure and protects against obesity and insulin resistance. Proc Natl Acad Sci U S A. 2012;109:5417–22.
Adams TD, Davidson LE, Litwin SE, Kolotkin RL, LaMonte MJ, Pendleton RC, et al. Health benefits of gastric bypass surgery after 6 years. JAMA. 2012;308:1122–31.
Meijer RI, van Wagensveld BA, Siegert CE, Eringa EC, Serne EH, Smulders YM. Bariatric surgery as a novel treatment for type 2 diabetes mellitus: a systematic review. Arch Surg. 2011;146:744–50.
Dick KJ, Nelson CP, Tsaprouni L, Sandling JK, Aissi D, Wahl S, Meduri E, Morange PE, Gagnon F, Grallert H, Waldenberger M, Peters A, Erdmann J, Hengstenberg C, Cambien F, Goodall AH, Ouwehand WH, Schunkert H, Thompson JR, Spector TD, Gieger C, Tregouet DA, Deloukas P, Samani NJ: DNA methylation and body-mass index: a genome-wide analysis. Lancet. 2014;383:1990–8
Relton CL, Groom A, St Pourcain B, Sayers AE, Swan DC, Embleton ND, et al. DNA methylation patterns in cord blood DNA and body size in childhood. PLoS One. 2012;7:e31821.
Walters RG, Coin LJ, Ruokonen A, de Smith AJ, El-Sayed Moustafa JS, Jacquemont S, et al. Rare genomic structural variants in complex disease: lessons from the replication of associations with obesity. PLoS One. 2013;8:e58048.
Mukherjee R, Yun JW. Long chain acyl CoA synthetase 1 and gelsolin are oppositely regulated in adipogenesis and lipogenesis. Biochem Biophys Res Commun. 2012;420:588–93.
Weems JC, Griesel BA, Olson AL. Class II histone deacetylases downregulate GLUT4 transcription in response to increased cAMP signaling in cultured adipocytes and fasting mice. Diabetes. 2012;61:1404–14.
Abu-Farha M, Tiss A, Abubaker J, Khadir A, Al-Ghimlas F, Al-Khairi I, et al. Proteomics analysis of human obesity reveals the epigenetic factor HDAC4 as a potential target for obesity. PLoS One. 2013;8:e75342.
Proverbio MC, Mangano E, Gessi A, Bordoni R, Spinelli R, Asselta R, et al. Whole genome SNP genotyping and exome sequencing reveal novel genetic variants and putative causative genes in congenital hyperinsulinism. PLoS One. 2013;8:e68740.
Yoshimura S, Gerondopoulos A, Linford A, Rigden DJ, Barr FA. Family-wide characterization of the DENN domain Rab GDP-GTP exchange factors. J Cell Biol. 2010;191:367–81.
Marat AL, Ioannou MS, McPherson PS. Connecdenn 3/DENND1C binds actin linking Rab35 activation to the actin cytoskeleton. Mol Biol Cell. 2012;23:163–75.
Marat AL, McPherson PS. The connecdenn family, Rab35 guanine nucleotide exchange factors interfacing with the clathrin machinery. J Biol Chem. 2010;285:10627–37.
Davey JR, Humphrey SJ, Junutula JR, Mishra AK, Lambright DG, James DE, et al. TBC1D13 is a RAB35 specific GAP that plays an important role in GLUT4 trafficking in adipocytes. Traffic. 2012;13:1429–41.
Tan JT, McLennan SV, Williams PF, Rezaeizadeh A, Lo LW, Bonner JG, et al. Connective tissue growth factor/CCN-2 is upregulated in epididymal and subcutaneous fat depots in a dietary-induced obesity model. Am J Physiol Endocrinol Metab. 2013;304:E1291–302.
Catalan V, Gomez-Ambrosi J, Rodriguez A, Ramirez B, Rotellar F, Valenti V, et al. Increased levels of calprotectin in obesity are related to macrophage content: impact on inflammation and effect of weight loss. Mol Med. 2011;17:1157–67.
Mortensen OH, Nielsen AR, Erikstrup C, Plomgaard P, Fischer CP, Krogh-Madsen R, et al. Calprotectin–a novel marker of obesity. PLoS One. 2009;4:e7419.
Sekimoto R, Kishida K, Nakatsuji H, Nakagawa T, Funahashi T, Shimomura I. High circulating levels of S100A8/A9 complex (calprotectin) in male Japanese with abdominal adiposity and dysregulated expression of S100A8 and S100A9 in adipose tissues of obese mice. Biochem Biophys Res Commun. 2012;419:782–9.
Sandoval J, Heyn H, Moran S, Serra-Musach J, Pujana MA, Bibikova M, et al. Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics. 2011;6:692–702.
Kolehmainen M, Salopuro T, Schwab US, Kekalainen J, Kallio P, Laaksonen DE, et al. Weight reduction modulates expression of genes involved in extracellular matrix and cell death: the GENOBIN study. Int J Obes (Lond). 2008;32:292–303.
Marquez-Quinones A, Mutch DM, Debard C, Wang P, Combes M, Roussel B, et al. Adipose tissue transcriptome reflects variations between subjects with continued weight loss and subjects regaining weight 6 mo after caloric restriction independent of energy intake. Am J Clin Nutr. 2010;92:975–84.
Viguerie N, Vidal H, Arner P, Holst C, Verdich C, Avizou S, et al. Adipose tissue gene expression in obese subjects during low-fat and high-fat hypocaloric diets. Diabetologia. 2005;48:123–31.
R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2012.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5:R80.
Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen et al. Minfi: A flexible and comprehensive Bioconductor package for the analysis of Infinium DNA Methylation microarrays. Bioinformatics. 2014;30(10)1363–1369.
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9.
Lowe R, Rakyan VK: Marmal-aid--a database for Infinium HumanMethylation450. BMC Bioinformatics. 2013;14:359.
Maechler M, Rousseeuw P, Struyf A, Hubert M, Hornik K: Cluster: Cluster Analysis Basics and Extensions.: R package version 1.14.3.; 2012.
Wang J, Duncan D, Shi Z, Zhang B. WEB-based GEne SeT AnaLysis toolkit (WebGestalt): update 2013. Nucleic Acids Res. 2013;41:W77–83.
Zhang B, Kirov S, Snoddy J. WebGestalt: an integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res. 2005;33:W741–8.