Abstract
Profiling genome-wide transcriptional changes with advanced high-throughput transcriptional profiling techniques has led to a revolution in biomedical science. It has been challenging to handle the massive data generated by these techniques and draw meaningful conclusions from it. Therefore, computational biologists have developed a number of innovative methods of varying complexity and effectiveness to analyze such complex data. Over the past decade, rich information in pathway repositories has attracted and motivated researchers to incorporate such existing biological knowledge into computational analysis tools to develop what is known as pathway enrichment analysis tools. This chapter describes a new sophisticated pathway enrichment tool that exploits topology of pathway as well as expression of significantly changed genes to identify biologically significant pathways for high-dimensional gene expression datasets. Also, we demonstrate the use of this tool to analyze gene expression data from a type 2 diabetes dataset to identify a list of significantly enriched metabolic pathways.
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References
Bauer-Mehren A, Furlong LI, Sanz F (2009) Pathway databases and tools for their exploitation: benefits, current limitations and challenges. Mol Syst Biol 5:290
Khatri P, Sirota M, Butte AJ (2012) Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput Biol 8(2):e1002375
Gao S, Wang X (2007) TAPPA: topological analysis of pathway phenotype association. Bioinformatics 23(22):3100–3102
Vert JP, Kanehisa M (2003) Extracting active pathways from gene expression data. Bioinformatics 19(Suppl 2):ii238–ii244
Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim J et al (2009) A novel signaling pathway impact analysis. Bioinformatics 25(1):75–82
Ibrahim MA, Jassim S, Cawthorne MA, Langlands K (2014) A MATLAB tool for pathway enrichment using a topology-based pathway regulation score. BMC Bioinformatics 15(1):358
Ibrahim MA, Jassim S, Cawthorne MA, Langlands K (2012) A topology-based score for pathway enrichment. J Comput Biol 19(5):563–573
Kanehisa M, Goto S, Kawashima S, Nakaya A (2001) The KEGG databases at GenomeNet. Nucleic Acids Res 2(1):42–46
Cheadle C, Vawter MP, Freed WJ, Becker KG (2003) Analysis of microarray data using Z score transformation. J Mol Diagn 5(2):73–81
Järvinen A-K, Hautaniemi S, Edgren H, Auvinen P, Saarela J, Kallioniemi O-P et al (2004) Are data from different gene expression microarray platforms comparable? Genomics 83(6):1164–1168
Li C, Wong W (2003) DNA-chip analyzer (dChip). http://www.springerlink.com/index/G5V0232463245R24.pdf
Pepper SD, Saunders EK, Edwards LE, Wilson CL, Miller CJ (2007) The utility of MAS5 expression summary and detection call algorithms. BMC Bioinformatics 8(1):273
Do JH, Choi D (2006) Normalization of microarray data: single-labeled and dual-labeled arrays. Mol Cells 22(3):254
Persaud SJ, Muller D, Belin VD, Kitsou-Mylona I, Asare-Anane H, Papadimitriou A et al (2007) The role of Arachidonic acid and its metabolites in insulin secretion from human islets of Langerhans. Diabetes 56(1):197–203
Prentki M, Nolan CJ (2006) Islet cell failure in type 2 diabetes. J Clin Invest 116(7):1802–1812
Yaney GC, Corkey BE (2003) Fatty acid metabolism and insulin secretion in pancreatic beta cells. Diabetologia 46(10):1297–1312
McGarry JD (2002) Banting lecture 2001 Dysregulation of fatty acid metabolism in the etiology of type 2 diabetes. Diabetes 51(1):7–18
Kim H-S, Hwang Y-C, Koo S-H, Park KS, Lee M-S, Kim K-W et al (2013) PPAR-γ activation increases insulin secretion through the up-regulation of the free fatty acid receptor GPR40 in pancreatic β-cells. PLoS One 8(1):e50128
Sugden MC, Holness MJ (2004) Potential role of peroxisome proliferator-activated receptor-α in the modulation of glucose-stimulated insulin secretion. Diabetes 53(1):S71–S81
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Ibrahim, M. (2020). Pathways Enrichment Analysis of Gene Expression Data in Type 2 Diabetes. In: Stocker, C. (eds) Type 2 Diabetes. Methods in Molecular Biology, vol 2076. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9882-1_7
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DOI: https://doi.org/10.1007/978-1-4939-9882-1_7
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