Browse > Article
http://dx.doi.org/10.9728/dcs.2018.19.9.1795

PRaDA : Web-based analyzer for Pathway Relation and Disease Associated SNP  

Yu, Kijin (Database/Bioinformatics Laboratory, School of Electrical & Computer Engineering, Chungbuk National University)
Park, Soo Ho (Database/Bioinformatics Laboratory, School of Electrical & Computer Engineering, Chungbuk National University)
Ryu, Keun Ho (Database/Bioinformatics Laboratory, School of Electrical & Computer Engineering, Chungbuk National University)
Publication Information
Journal of Digital Contents Society / v.19, no.9, 2018 , pp. 1795-1801 More about this Journal
Abstract
Genome-Wide Association Study (GWAS) have been used to identify susceptibility genes for complex human diseases and many recent studies succeed to report common genetic factors for various diseases. Unfortunately, it is hard to understand all biological functions and mechanisms around the complex disease with GWAS only although the number of known associated genes with diseases is increased drastically because GWAS is a single locus based approach while not a gene but numerous factors may affect a disease associated pathways. PRaDA generates a combined report with genes, pathways and Gene Ontology (GO) using single nucleotide polymorphism (SNP) analysis output. The PRaDA reports not only directly associated pathways but also functionally related ones for identifying accumulated effects of low p-value SNPs. Through integrated information including indirect functional effects, user could have insights of overall disease mechanisms and markers.
Keywords
SNP; GWAS; Gene interaction; Biological pathway; Gene set enrichment analysis;
Citations & Related Records
연도 인용수 순위
  • Reference
1 P. Y. P. Kao, K. H. Leung, L. W. C. Chan, S. P. Yip, M. K. H. Yap, "Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions", Biochimica et Biophysica Acta, Vol. 1861, Issue. 2, pp. 335-353, 2017.   DOI
2 S. E. Kim, H. Kim, Y. Yun, S. G. Heo, J. Cho, M. Kwon, Y. Chang, S. Ryu, H. Shin, C. Shin, N. H. Cho, Y. A. Sung, H. Kim, "Meta-analysis of genome-wide SNP- and pathway-based associations for facets of neuroticism", Journal of Human Genetics, Vol. 62, pp. 903-909, 2017.   DOI
3 J. Wu, X. Mao, T. Cai, J. Luo, L. Wei, "KOBAS server: a web-based platform for automated annotation and pathway identification", Nucleic Acids Research, Vol. 34, W720-724, 2006.   DOI
4 L. Weng, F. Macciardi, A. Subramanian, G. Guffanti, S. G. Potkin, Z. Yu, X. Xie, "SNP-based pathway enrichment analysis for genome-wide association studies", BMC Bioinformatics, 12:99, 2011.   DOI
5 I. Medina, D. Montaner, N. Bonifaci, M. A. Pujana, J. Carbonell, J. Tarraga, F. Al-Shahrour, J. Dopazo, "Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies", Nucleic Acids Research, Vol. 37, W340-344, 2009.   DOI
6 P. Holmans, E. K. Green, J. S. Pahwa, M. A. Ferreira, S. M. Purcell, P. Sklar, Wellcome Trust Case-Control Consortium, M. J. Owen, M. C. O'Donovan, N. Craddock, "Gene ontology analysis of GWA study data sets provides insights into the biology of bipolar disorder", American Journal of Human Genetics, Vol. 85, pp. 13-24, 2009.   DOI
7 D. Zamar, B. Tripp, G. Ellis, D. Daley, "Path: a tool to facilitate pathway-based genetic association analysis", Bioinformatics, Vol. 25, pp. 2444-2446, 2009.   DOI
8 R. M. Cantor, K. Lange, J. S. Sinsheimer, "Prioritizing GWAS Results: A review of statistical methods and recommendations for their application", American Journal of Human Genetics, Vol. 86, pp. 6-22, 2010.   DOI
9 K. Zhang, S. Cui, S. Chang, L. Zhang, J. Wang, "i-GSEA4GWAS: a web server for identification of pathways/gene sets associated with traits by applying an improved gene set enrichment analysis to genome-wide association study", Nucleic Acids Research, Vol. 38, W90-95, 2010.   DOI
10 E. Cirillo, M. Kutmon, M. G. Hernandez, T. Hooimeijer, M. E. Adriaens, L. M. T. Eijssen, L. D. Parnell, S. L. Coort, C. T. Evelo, "From SNPs to pathways: Biological interpretation of type 2 diabetes (T2DM) genome wide association study (GWAS) results", PLoS ONE, Vol. 13, No. 4, 2018.
11 D. W. Huang, B. T. Sherman, R. A. Lempicki, "Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists", Nucleic Acids Res, Vol. 37, pp. 1-13, 2009.   DOI
12 G. Peng, L. Luo, H. Siu, Y. Zhu, P. Hu, S. Hong, J. Zhao, X. Zhou, J. D. Reveille, L. Jin, C. I. Amos, M. Xiong, "Gene and pathway-based second-wave analysis of genome-wide association studies", European Journal of Human Genetics, Vol. 18, pp. 111-117, 2010.   DOI
13 K. Sidiropoulos, G. Viteri, C. Sevilla, S. Jupe, M. Webber, M. Orlic-Milacic, B. Jassal, B. May, V. Shamovsky, C. Duenas, K. Rothfels, L. Matthews, H. Song, L. Stein, R. Haw, P. D'Eustachio, P. Ping, H. Hermjakob, A. Fabregat, "Reactome enhanced pathway visualization", Bioinformatics, Vol. 33, Issue. 21, pp. 3461-3467, 2017.   DOI
14 H. J. Ban, J. Y. Heo, K. S. Oh, K.J. Park, "Identification of type 2 diabetes-associated combination of SNPs using support vector machine", BMC Genetics, Vol. 23, pp. 11-26, 2010.
15 K. Zhang, S. Chang, S. Cui, L. Guo, L. Zhang, J. Wang, "ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework", Nucleic Acids Research, Vol. 39, W437-443, 2011.   DOI
16 D. F. Schwarz, O. Hädicke, J. Erdmann, A. Ziegler, D. Bayer, S. Moller, "SNPtoGO: characterizing SNPs by enriched GO terms", Bioinformatics, Vol. 24, pp. 146-148, 2008.   DOI
17 dbSNP : a database of single nucleotide polymorphisms [Internet]. Available: http://www.ncbi.nlm.nih.gov/projects/SNP.
18 refGene [Internet]. Available: http://www.ncbi.nlm.nih.gov/RefSeq.
19 Kyoto Encyclopedia of Genes and Genomes (KEGG) [Internet]. Available: http://www.genome.jp/kegg.
20 A. Subramanian, P. Tamayo, V. K. Mootha, S. Mukherjee, B. L. Ebert, M.A. Gillette, A. Paulovich, S. L. Pomeroy, T. R. Golub, E. S. Lander, J. P. Mesirov, "Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles", Proc Natl Acad Sci USA, Vol. 102, pp. 15545-15550, 2005.   DOI
21 Gene Ontology database [Internet]. Available: http://www.geneontology.org.
22 A. Hamosh, A. F. Scott, J. S. Amberger, C. A. Bocchini, V. A. McKusick, "Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders", Nucleic Acids Research, Vol. 33, Issue. supp. l_1, pp. D514-D517, 2005.
23 M. A. Garcia-Campos, J. Espinal-Enriquez, E. Hernandez-Lemus, "Pathway Analysis: State of the Art", Frontiers in Physiology, 6:383, 2015.
24 S. Purcell, B. Neale, K. Todd-Brown, L. Thomas, M. A. R. Ferreira, D. Bender, J. Maller, P. Sklar, P. I. W. de Bakker, M. J. Daly, P. C. Sham, "PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses", The American Journal of Human Genetics, Vol. 81, Issue. 3, pp. 559-575, 2007.   DOI
25 S. R. Chowbina, X. Wu, F. Zhang, P. M. Li, R. Pandey, H. N. Kasamsetty, J.Y. Chen, "HPD: an online integrated human pathway database enabling systems biology studies", BMC Bioinformatics, Vol. 10, Suppl 11:S5, 2009.