Network-assisted analysis to prioritize GWAS results: Principles, methods and perspectives

Human Genetics

Volumn 133, Issue 2, 2014, Pages 125-138

  Jia, Peilin ^a   Zhao, Zhongming ^a  

^a VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEIN;

ALGORITHM; DATA ANALYSIS; DISEASE ASSOCIATION; EPIGENETICS; GENE; GENETIC ASSOCIATION; GENETIC RISK; GENOME; GENOTYPE ENVIRONMENT INTERACTION; HERITABILITY; HUMAN; METHODOLOGY; NETWORK ASSISTED ANALYSIS; PATHWAY BASED ANALYSIS; PHENOTYPE; PRIORITY JOURNAL; PROTEIN PROTEIN INTERACTION; QUANTITATIVE ANALYSIS; QUANTITATIVE TRAIT LOCUS; REVIEW; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL ANALYSIS;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATA MINING; DATABASES, GENETIC; GENETIC DISEASES, INBORN; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; HUMANS; INTERNET; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84893174522     PISSN: 03406717     EISSN: 14321203     Source Type: Journal    
DOI: 10.1007/s00439-013-1377-1     Document Type: Review

References (100)

1. Akula N, Baranova A, Seto D, Solka J, Nalls MA, Singleton A, Ferrucci L, Tanaka T, Bandinelli S, Cho YS, Kim YJ, Lee JY, Han BG, McMahon FJ (2011) A network-based approach to prioritize results from genome-wide association studies. PLoS ONE 6:e24220
2. Arning A, Hiersche M, Witten A, Kurlemann G, Kurnik K, Manner D, Stoll M, Nowak-Gottl U (2012) A genome-wide association study identifies a gene network of ADAMTS genes in the predisposition to pediatric stroke. Blood 120:5231-5236
3. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25:25-29
4. Askland K, Read C, Moore J (2009) Pathways-based analyses of whole-genome association study data in bipolar disorder reveal genes mediating ion channel activity and synaptic neurotransmission. Hum Genet 125:63-79
5. Askland K, Read C, O'Connell C, Moore JH (2012) Ion channels and schizophrenia: a gene set-based analytic approach to GWAS data for biological hypothesis testing. Hum Genet 131:373-391
6. Barabasi AL, Gulbahce N, Loscalzo J (2011) Network medicine: a network-based approach to human disease. Nat Rev Genet 12:56-68
7. Baranzini SE, Galwey NW, Wang J, Khankhanian P, Lindberg R, Pelletier D, Wu W, Uitdehaag BM, Kappos L, Polman CH, Matthews PM, Hauser SL, Gibson RA, Oksenberg JR, Barnes MR (2009) Pathway and network-based analysis of genome-wide association studies in multiple sclerosis. Hum Mol Genet 18:2078-2090
8. Baranzini SE, Srinivasan R, Khankhanian P, Okuda DT, Nelson SJ, Matthews PM, Hauser SL, Oksenberg JR, Pelletier D (2010) Genetic variation influences glutamate concentrations in brains of patients with multiple sclerosis. Brain 133:2603-2611
9. Barshir R, Basha O, Eluk A, Smoly IY, Lan A, Yeger-Lotem E (2013) The TissueNet database of human tissue protein-protein interactions. Nucleic Acids Res 41:D841-D844
10. Ben-David E, Shifman S (2012) Networks of neuronal genes affected by common and rare variants in autism spectrum disorders. PLoS Genet 8:e1002556
11. Bornigen D, Tranchevent LC, Bonachela-Capdevila F, Devriendt K, De Moor B, De Causmaecker P, Moreau Y (2012) An unbiased evaluation of gene prioritization tools. Bioinformatics 28:3081-3088
12. Braun P (2012) Interactome mapping for analysis of complex phenotypes: insights from benchmarking binary interaction assays. Proteomics 12:1499-1518
13. Burcu B-G, Osman Ugur S (2011) A new methodology to associate SNPs with human diseases according to their pathway related context. PLoS ONE 6:e26277
14. Burcu B-G, Osman Ugur S (2012) Identification of SNP targeted pathways from genome-wide association study (GWAS) data. doi: 10.1038/protex.2012.019
15. Cantor RM, Lange K, Sinsheimer JS (2010) Prioritizing GWAS results: a review of statistical methods and recommendations for their application. Am J Hum Genet 86:6-22
16. Chatr-Aryamontri A, Breitkreutz BJ, Heinicke S, Boucher L, Winter A, Stark C, Nixon J, Ramage L, Kolas N, O'Donnell L, Reguly T, Breitkreutz A, Sellam A, Chen D, Chang C, Rust J, Livstone M, Oughtred R, Dolinski K, Tyers M (2013) The BioGRID interaction database: 2013 update. Nucleic Acids Res 41:D816-D823
17. Chen LS, Hutter CM, Potter JD, Liu Y, Prentice RL, Peters U, Hsu L (2010) Insights into colon cancer etiology via a regularized approach to gene set analysis of GWAS data. Am J Hum Genet 86:860-871
18. Chuang HY, Lee E, Liu YT, Lee D, Ideker T (2007) Network-based classification of breast cancer metastasis. Mol Syst Biol 3:140
19. Cotsapas C, Voight BF, Rossin E, Lage K, Neale BM, Wallace C, Abecasis GR, Barrett JC, Behrens T, Cho J, De Jager PL, Elder JT, Graham RR, Gregersen P, Klareskog L, Siminovitch KA, van Heel DA, Wijmenga C, Worthington J, Todd JA, Hafler DA, Rich SS, Daly MJ (2011) Pervasive sharing of genetic effects in autoimmune disease. PLoS Genet 7:e1002254
20. Curtis D, Vine AE, Knight J (2008) A simple method for assessing the strength of evidence for association at the level of the whole gene. Adv Appl Bioinform Chem 1:115-120
21. Dering C, Hemmelmann C, Pugh E, Ziegler A (2011) Statistical analysis of rare sequence variants: an overview of collapsing methods. Genet Epidemiol 35(Suppl 1):S12-S17
22. Detera-Wadleigh SD, Akula N (2011) A systems approach to the biology of mood disorders through network analysis of candidate genes. Pharmacopsychiatry 44(Suppl 1):S35-S42
23. Elbers CC, van der Schouw YT, Wijmenga C, Onland-Moret NC (2009) Comment on: Perry et al. (2009) Interrogating type 2 diabetes genome-wide association data using a biological pathway-based approach. Diabetes;58:1463-1467. Diabetes 58:e9 (author reply e10)
24. Farber CR (2010) Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data. J Bone Miner Res 25:2359-2367
25. Farber CR (2013) Systems-level analysis of genome-wide association data. G3 (Bethesda) 3:119-129
26. Fehringer G, Liu G, Briollais L, Brennan P, Amos CI, Spitz MR, Bickeboller H, Wichmann HE, Risch A, Hung RJ (2012) Comparison of pathway analysis approaches using lung cancer GWAS data sets. PLoS ONE 7:e31816
27. Garcia-Alonso L, Alonso R, Vidal E, Amadoz A, de Maria A, Minguez P, Medina I, Dopazo J (2012) Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments. Nucleic Acids Res 40:e158
28. Gibson G (2010) Hints of hidden heritability in GWAS. Nat Genet 42:558-560
29. Gibson G (2011) Rare and common variants: twenty arguments. Nat Rev Genet 13:135-145
30. Gillis J, Pavlidis P (2012) "Guilt by association" is the exception rather than the rule in gene networks. PLoS Comput Biol 8:e1002444
31. Gilman SR, Iossifov I, Levy D, Ronemus M, Wigler M, Vitkup D (2011) Rare de novo variants associated with autism implicate a large functional network of genes involved in formation and function of synapses. Neuron 70:898-907
32. Gilman SR, Chang J, Xu B, Bawa TS, Gogos JA, Karayiorgou M, Vitkup D (2012) Diverse types of genetic variation converge on functional gene networks involved in schizophrenia. Nat Neurosci 15:1723-1728
33. Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, Manolio TA (2009) Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci USA 106:9362-9367
34. Holmans P, Green EK, Pahwa JS, Ferreira MA, Purcell SM, Sklar P, Owen MJ, O'Donovan MC, Craddock N (2009) Gene ontology analysis of GWA study data sets provides insights into the biology of bipolar disorder. Am J Hum Genet 85:13-24
35. Hu T, Sinnott-Armstrong NA, Kiralis JW, Andrew AS, Karagas MR, Moore JH (2011) Characterizing genetic interactions in human disease association studies using statistical epistasis networks. BMC Bioinforma 12:364
36. Ideker T, Ozier O, Schwikowski B, Siegel AF (2002) Discovering regulatory and signalling circuits in molecular interaction networks. Bioinformatics 18(Suppl 1):S233-S240
37. International Multiple Sclerosis Genetics Consortium (2013) Network-based multiple sclerosis pathway analysis with GWAS data from 15,000 cases and 30,000 controls. Am J Hum Genet. doi: 10.1016/j.ajhg.2013.04.019
38. Jensen MK, Pers TH, Dworzynski P, Girman CJ, Brunak S, Rimm EB (2011) Protein interaction-based genome-wide analysis of incident coronary heart disease. Circ Cardiovasc Genet 4:549-556
39. Jia P, Zhao Z (2012) Searching joint association signals in CATIE schizophrenia genome-wide association studies through a refined integrative network approach. BMC Genomics 1471-2164-13-S6-S15
40. Jia P, Tian J, Zhao Z (2010a) Assessing gene length biases in gene set analysis of genome-wide association studies. Int J Comput Biol Drug Des 3:297-310
41. Jia P, Wang L, Meltzer HY, Zhao Z (2010b) Common variants conferring risk of schizophrenia: a pathway analysis of GWAS data. Schizophr Res 122:38-42
42. Jia P, Wang L, Meltzer HY, Zhao Z (2011a) Pathway-based analysis of GWAS datasets: effective but caution required. Int J Neuropsychopharmacol 14:567-572
43. Jia P, Zheng S, Long J, Zheng W, Zhao Z (2011b) dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks. Bioinformatics 27:95-102
44. Jia P, Liu Y, Zhao Z (2012a) Integrative pathway analysis of genome-wide association studies and gene expression data in prostate cancer. BMC Syst Biol 6(Suppl 3):S13
45. Jia P, Wang L, Fanous AH, Chen X, Kendler KS, Zhao Z (2012b) A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia. J Med Genet 49:96-103
46. Jia P, Wang L, Fanous AH, Pato CN, Edwards TL, Zhao Z (2012c) Network-assisted investigation of combined causal signals from genome-wide association studies in schizophrenia. PLoS Comput Biol 8:e1002587
47. Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 38:D355-D360
48. Klein RJ, Zeiss C, Chew EY, Tsai JY, Sackler RS, Haynes C, Henning AK, SanGiovanni JP, Mane SM, Mayne ST, Bracken MB, Ferris FL, Ott J, Barnstable C, Hoh J (2005) Complement factor H polymorphism in age-related macular degeneration. Science 308:385-389
49. Kohler S, Bauer S, Horn D, Robinson PN (2008) Walking the interactome for prioritization of candidate disease genes. Am J Hum Genet 82:949-958
50. Kondor RI, Lafferty JD (2002) Diffusion kernels on graphs and other discrete input spaces. In: Proceedings of the nineteenth international conference on machine learning. Morgan Kaufmann, San Francisco, pp 315-322
51. Lage K, Karlberg EO, Storling ZM, Olason PI, Pedersen AG, Rigina O, Hinsby AM, Tumer Z, Pociot F, Tommerup N, Moreau Y, Brunak S (2007) A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat Biotechnol 25:309-316
52. Lee I, Blom UM, Wang PI, Shim JE, Marcotte EM (2011) Prioritizing candidate disease genes by network-based boosting of genome-wide association data. Genome Res 21:1109-1121
53. Li J, Zimmerman LJ, Park BH, Tabb DL, Liebler DC, Zhang B (2009) Network-assisted protein identification and data interpretation in shotgun proteomics. Mol Syst Biol 5:303
54. Li MX, Gui HS, Kwan JS, Sham PC (2011) GATES: a rapid and powerful gene-based association test using extended Simes procedure. Am J Hum Genet 88:283-293
55. Liu JZ, McRae AF, Nyholt DR, Medland SE, Wray NR, Brown KM, Hayward NK, Montgomery GW, Visscher PM, Martin NG, Macgregor S (2010) A versatile gene-based test for genome-wide association studies. Am J Hum Genet 87:139-145
56. Liu Y, Patel S, Nibbe R, Maxwell S, Chowdhury SA, Koyuturk M, Zhu X, Larkin EK, Buxbaum SG, Punjabi NM, Gharib SA, Redline S, Chance MR (2011) Systems biology analyses of gene expression and genome wide association study data in obstructive sleep apnea. Pac Symp Biocomput 14-25
57. Ma L, Clark AG, Keinan A (2013) Gene-based testing of interactions in association studies of quantitative traits. PLoS Genet 9:e1003321
58. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, Cho JH, Guttmacher AE, Kong A, Kruglyak L, Mardis E, Rotimi CN, Slatkin M, Valle D, Whittemore AS, Boehnke M, Clark AG, Eichler EE, Gibson G, Haines JL, Mackay TF, McCarroll SA, Visscher PM (2009) Finding the missing heritability of complex diseases. Nature 461:747-753
59. McKinney BA, Pajewski NM (2011) Six degrees of epistasis: statistical network models for GWAS. Front Genet 2:109
60. McKinney BA, Crowe JE, Guo J, Tian D (2009) Capturing the spectrum of interaction effects in genetic association studies by simulated evaporative cooling network analysis. PLoS Genet 5:e1000432
61. Mukhopadhyay I, Feingold E, Weeks DE, Thalamuthu A (2010) Association tests using kernel-based measures of multi-locus genotype similarity between individuals. Genet Epidemiol 34:213-221
62. Neale BM, Kou Y, Liu L, Ma'ayan A, Samocha KE, Sabo A, Lin CF, Stevens C, Wang LS, Makarov V, Polak P, Yoon S, Maguire J, Crawford EL, Campbell NG, Geller ET, Valladares O, Schafer C, Liu H, Zhao T, Cai G, Lihm J, Dannenfelser R, Jabado O, Peralta Z, Nagaswamy U, Muzny D, Reid JG, Newsham I, Wu Y, Lewis L, Han Y, Voight BF, Lim E, Rossin E, Kirby A, Flannick J, Fromer M, Shakir K, Fennell T, Garimella K, Banks E, Poplin R, Gabriel S, DePristo M, Wimbish JR, Boone BE, Levy SE, Betancur C, Sunyaev S, Boerwinkle E, Buxbaum JD, Cook EH Jr, Devlin B, Gibbs RA, Roeder K, Schellenberg GD, Sutcliffe JS, Daly MJ (2012) Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 485:242-245
63. Ng S, Collisson EA, Sokolov A, Goldstein T, Gonzalez-Perez A, Lopez-Bigas N, Benz C, Haussler D, Stuart JM (2012) PARADIGM-SHIFT predicts the function of mutations in multiple cancers using pathway impact analysis. Bioinformatics 28:i640-i646
64. Nitsch D, Tranchevent LC, Thienpont B, Thorrez L, Van Esch H, Devriendt K, Moreau Y (2009) Network analysis of differential expression for the identification of disease-causing genes. PLoS ONE 4:e5526
65. Pedroso I, Lourdusamy A, Rietschel M, Nothen MM, Cichon S, McGuffin P, Al-Chalabi A, Barnes MR, Breen G (2012) Common genetic variants and gene-expression changes associated with bipolar disorder are over-represented in brain signaling pathway genes. Biol Psychiatry 72:311-317
66. Peng G, Luo L, Siu H, Zhu Y, Hu P, Hong S, Zhao J, Zhou X, Reveille JD, Jin L, Amos CI, Xiong M (2010) Gene and pathway-based second-wave analysis of genome-wide association studies. Eur J Hum Genet 18:111-117
67. Perry JR, McCarthy MI, Hattersley AT, Zeggini E, Weedon MN, Frayling TM (2009) Interrogating type 2 diabetes genome-wide association data using a biological pathway-based approach. Diabetes 58:1463-1467
68. Ragnedda G, Disanto G, Giovannoni G, Ebers GC, Sotgiu S, Ramagopalan SV (2012) Protein-protein interaction analysis highlights additional loci of interest for multiple sclerosis. PLoS ONE 7:e46730
69. Raj T, Shulman JM, Keenan BT, Chibnik LB, Evans DA, Bennett DA, Stranger BE, De Jager PL (2012) Alzheimer disease susceptibility loci: evidence for a protein network under natural selection. Am J Hum Genet 90:720-726
70. Ramanan VK, Shen L, Moore JH, Saykin AJ (2012) Pathway analysis of genomic data: concepts, methods, and prospects for future development. Trends Genet 28:323-332
71. Raychaudhuri S, Plenge RM, Rossin EJ, Ng AC, Purcell SM, Sklar P, Scolnick EM, Xavier RJ, Altshuler D, Daly MJ (2009) Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions. PLoS Genet 5:e1000534
72. Rossin EJ, Lage K, Raychaudhuri S, Xavier RJ, Tatar D, Benita Y, Cotsapas C, Daly MJ (2011) Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology. PLoS Genet 7:e1001273
73. Ruano D, Abecasis GR, Glaser B, Lips ES, Cornelisse LN, de Jong AP, Evans DM, Davey Smith G, Timpson NJ, Smit AB, Heutink P, Verhage M, Posthuma D (2010) Functional gene group analysis reveals a role of synaptic heterotrimeric G proteins in cognitive ability. Am J Hum Genet 86:113-125
74. Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ, Ercan-Sencicek AG, DiLullo NM, Parikshak NN, Stein JL, Walker MF, Ober GT, Teran NA, Song Y, El-Fishawy P, Murtha RC, Choi M, Overton JD, Bjornson RD, Carriero NJ, Meyer KA, Bilguvar K, Mane SM, Sestan N, Lifton RP, Gunel M, Roeder K, Geschwind DH, Devlin B, State MW (2012) De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 485:237-241
75. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498-2504
76. Sullivan PF, Lin D, Tzeng JY, van den Oord E, Perkins D, Stroup TS, Wagner M, Lee S, Wright FA, Zou F, Liu W, Downing AM, Lieberman J, Close SL (2008) Genomewide association for schizophrenia in the CATIE study: results of stage 1. Mol Psychiatry 13:570-584
77. Sun YV (2012) Integration of biological networks and pathways with genetic association studies. Hum Genet 131(10):1677-1686
78. Sun J, Jia P, Fanous AH, Webb BT, van den Oord EJ, Chen X, Bukszar J, Kendler KS, Zhao Z (2009) A multi-dimensional evidence-based candidate gene prioritization approach for complex diseases-schizophrenia as a case. Bioinformatics 25:2595-6602
79. Vaske CJ, Benz SC, Sanborn JZ, Earl D, Szeto C, Zhu J, Haussler D, Stuart JM (2010) Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM. Bioinformatics 26:i237-i245
80. Vidal M, Cusick ME, Barabasi AL (2011) Interactome networks and human disease. Cell 144:986-998
81. Wang K, Abbott D (2008) A principal components regression approach to multilocus genetic association studies. Genet Epidemiol 32:108-118
82. Wang K, Li M, Bucan M (2007) Pathway-based approaches for analysis of genomewide association studies. Am J Hum Genet 81:1278-1283
83. Wang K, Zhang H, Kugathasan S, Annese V, Bradfield JP, Russell RK, Sleiman PM, Imielinski M, Glessner J, Hou C, Wilson DC, Walters T, Kim C, Frackelton EC, Lionetti P, Barabino A, Van Limbergen J, Guthery S, Denson L, Piccoli D, Li M, Dubinsky M, Silverberg M, Griffiths A, Grant SF, Satsangi J, Baldassano R, Hakonarson H (2009) Diverse genome-wide association studies associate the IL12/IL23 pathway with Crohn disease. Am J Hum Genet 84:399-405
84. Wang K, Li M, Hakonarson H (2010) Analysing biological pathways in genome-wide association studies. Nat Rev Genet 11:843-854
85. Wang L, Jia P, Wolfinger RD, Chen X, Grayson BL, Aune TM, Zhao Z (2011a) An efficient hierarchical generalized linear mixed model for pathway analysis of genome-wide association studies. Bioinformatics 27:686-692
86. Wang L, Jia P, Wolfinger RD, Chen X, Zhao Z (2011b) Gene set analysis of genome-wide association studies: methodological issues and perspectives. Genomics 98:1-8
87. Wang Q, Jia P, Wang L, Feingold E, Cuenco KT, Marazita ML, Zhao Z (2013) Association signals unveiled by a comprehensive gene set enrichment analysis of dental caries genome-wide association studies. PLoS ONE 8:e72653
88. Wessel J, Schork NJ (2006) Generalized genomic distance-based regression methodology for multilocus association analysis. Am J Hum Genet 79:792-806
89. Wu C, Cui Y (2013) Boosting signals in gene-based association studies via efficient SNP selection. Brief Bioinform
90. Wu J, Vallenius T, Ovaska K, Westermarck J, Makela TP, Hautaniemi S (2009) Integrated network analysis platform for protein-protein interactions. Nat Methods 6:75-77
91. Wu G, Feng X, Stein L (2010a) A human functional protein interaction network and its application to cancer data analysis. Genome Biol 11:R53
92. Wu MC, Kraft P, Epstein MP, Taylor DM, Chanock SJ, Hunter DJ, Lin X (2010b) Powerful SNP-set analysis for case-control genome-wide association studies. Am J Hum Genet 86:929-942
93. Xiong Q, Ancona N, Hauser ER, Mukherjee S, Furey TS (2012) Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets. Genome Res 22:386-397
94. Xu B, Ionita-Laza I, Roos JL, Boone B, Woodrick S, Sun Y, Levy S, Gogos JA, Karayiorgou M (2012) De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia. Nat Genet 44:1365-1369
95. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42:565-569
96. Yang J, Manolio TA, Pasquale LR, Boerwinkle E, Caporaso N, Cunningham JM, de Andrade M, Feenstra B, Feingold E, Hayes MG, Hill WG, Landi MT, Alonso A, Lettre G, Lin P, Ling H, Lowe W, Mathias RA, Melbye M, Pugh E, Cornelis MC, Weir BS, Goddard ME, Visscher PM (2011) Genome partitioning of genetic variation for complex traits using common SNPs. Nat Genet 43:519-525
97. Zaykin DV, Zhivotovsky LA, Westfall PH, Weir BS (2002) Truncated product method for combining P-values. Genet Epidemiol 22:170-185
98. Zaykin DV, Zhivotovsky LA, Czika W, Shao S, Wolfinger RD (2007) Combining p-values in large-scale genomics experiments. Pharm Stat 6:217-226
99. Zhang M, Liang L, Morar N, Dixon AL, Lathrop GM, Ding J, Moffatt MF, Cookson WO, Kraft P, Qureshi AA, Han J (2012) Integrating pathway analysis and genetics of gene expression for genome-wide association study of basal cell carcinoma. Hum Genet 131:615-623
100. Zhu J, Sova P, Xu Q, Dombek KM, Xu EY, Vu H, Tu Z, Brem RB, Bumgarner RE, Schadt EE (2012) Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation. PLoS Biol 10:e1001301