TY - GEN
T1 - Identifying biologically significant pathways by gene set enrichment analysis using fisher's criterion
AU - Kim, Jaeyoung
AU - Lee, Hyungmin
AU - Shin, Miyoung
PY - 2008
Y1 - 2008
N2 - Gene set enrichment analysis (GSEA) is a computational method to identify statistically significant genesets showing differential expression between two groups. In particular, unlike other previous approaches, this enables us to uncover their biological meanings in an elegant way by providing a unified analytical framework that employs a priori known biological knowledges along with gene expression profiles during the analysis procedure. For original GSEA, all the genes in a given dataset are ordered by the signal-to-noise ratio of their microarray expression profiles between two groups and then further analyses are proceeded. Despite of its impressive results in previous studies with original GSEA, however, gene ranking by the signal-to-noise ratio makes it difficult to extract both highly up-regulated genes and highly down-regulated genes at a time as significant genes, which may not reflect such situations as incurred in metabolic and signaling pathways. Thus, it is necessary to make further investigation for better finding of biologically significant pathways. To deal with this problem, in this article, we explore the method of gene set enrichment analysis with Fisher's criterion for gene ranking, named FC-GSEA, and evaluate its effects made in Leukemia related pathway analyses.
AB - Gene set enrichment analysis (GSEA) is a computational method to identify statistically significant genesets showing differential expression between two groups. In particular, unlike other previous approaches, this enables us to uncover their biological meanings in an elegant way by providing a unified analytical framework that employs a priori known biological knowledges along with gene expression profiles during the analysis procedure. For original GSEA, all the genes in a given dataset are ordered by the signal-to-noise ratio of their microarray expression profiles between two groups and then further analyses are proceeded. Despite of its impressive results in previous studies with original GSEA, however, gene ranking by the signal-to-noise ratio makes it difficult to extract both highly up-regulated genes and highly down-regulated genes at a time as significant genes, which may not reflect such situations as incurred in metabolic and signaling pathways. Thus, it is necessary to make further investigation for better finding of biologically significant pathways. To deal with this problem, in this article, we explore the method of gene set enrichment analysis with Fisher's criterion for gene ranking, named FC-GSEA, and evaluate its effects made in Leukemia related pathway analyses.
UR - http://www.scopus.com/inward/record.url?scp=62449163207&partnerID=8YFLogxK
U2 - 10.1109/FGCN.2008.212
DO - 10.1109/FGCN.2008.212
M3 - Conference contribution
AN - SCOPUS:62449163207
SN - 9780769534312
T3 - Proceedings of the 2008 2nd International Conference on Future Generation Communication and Networking, FGCN 2008 and BSBT 2008: 2008 International Conference on Bio-Science and Bio-Technology
SP - 63
EP - 66
BT - Proceedings of the 2008 2nd International Conference on Future Generation Communication and Networking, FGCN 2008 and BSBT 2008
T2 - 2008 International Conference on Bio-Science and Bio-Technology, BSBT 2008, held in conjunction with 2008 2nd International Conference on Future Generation Communication and Networking, FGCN 2008
Y2 - 13 December 2008 through 15 December 2008
ER -