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題名 運用充分資料縮減法於基因組分析
Application of the Sufficient Dimension Reduction to Gene Set Analysis
作者 蔡志旻
Tsai, Chih Min
貢獻者 薛慧敏
蔡志旻
Tsai, Chih Min
關鍵詞 外顯特徵
基因組分析
切片平均變異數估計法
邊際維度檢定法
日期 2013
上傳時間 21-Jul-2014 15:36:41 (UTC+8)
摘要 生物現象多是由許多基因共同作用產生的結果，以基因組分析方法探討外顯特徵變數與基因組的相關性將更能幫助研究人員了解生物體的作用機制。目前已發展的基因組分析方法大多是針對離散型態的外顯特徵變數，在臨床醫學上，很多疾病的外顯特徵為連續型變數。本研究之目的即為發展運用在連續型外顯特徵變數的基因組分析方法。本文將考慮切片平均變異數估計法進行充分維度縮減的方法，原先被用來決定原始資料被縮減的程度之邊際維度檢定法將被運用於基因組分析方法。除了原有的邊際維度檢定法之外，我們另提出一改良的邊際維度檢定法，並以排列重抽法獲得這兩種檢定方法之排列顯著值。本文將透過電腦模擬以及實例分析來評估兩種邊際維度檢定法，同時也將列入Dinu等學者(2013)所發展的線性組合檢定法之結果以作為比較。
參考文獻 Becker, C. and Gather, U. (2007) A note on the choice of the number of slices in sliced inverse regression. Technical Report, 475.

Biernacka, J.M., Geske, J., Jenkins, G.D., Colby, C., Rider, D.N., Karpyak, V.M., Choi, D. and Fridley, B.L. (2012) Genome-wide gene-set analysis for identification of pathways associated with alcohol dependence. International Journal of Neuropsychopharmacology, 16, 271-278.

Chang, S., Hursting, S.D., Contois, J.H., Strom, S.S., Yamamura, Y., Babaian, R.J., Troncoso, P., Scardino, P.T., Wheeler, T.M., Amos, C.I. and Spitz, M.R. (2001) Leptin and prostate cancer. The Prostate, 46, 62-67.

Chen, J., Pamuklar, Z., Spagnoli, A. and Torquati, A. (2012) Serum leptin levels are inversely correlated with omental gene expression of adiponectin and markedly decreased after gastric bypass surgery. Surg Endosc, 26, 1476-1480.

Cook, R.D. (1996) Graphics for regression with a binary response. Journal of the American Statistical Association, 91, 983-992.

Cook, R.D. and Lee, H. (1999) Dimension reduction in binary response regression. Journal of the American Statistical Association, 94, 1187-1200.
Cook, R.D. and Weisberg, S. (1991) Discussion of ”Sliced Inverse Regression for Dimension Reduction.” Journal of the American Statistical Association, 86, 328-332.

Dinu, I., Potter, J.D., Mueller, T., Liu, Q., Adewale, A.J., Jhangri, G.S., Einecke, G., Famulski, K.S., Halloran, P. and Yasui, Y. (2007) Improving gene set analysis of microarray data by SAM-GS. Bioinformatics, 8, 242.

Dinu, I., Wang, X., Kelemen, L.E., Vatanpour, S. and Pyne, S. (2013) Linear combination test for gene set analysis of a continuous phenotype. BMC Bioinformatics, 14, 212.

Eid, M.A., Kumar, M.V., Iczkowski, K.A., Bostwick, D.G. and Tindall, D.J. (1998) Expression of early growth response genes in human prostate cancer. Cancer Res, 58, 2461-2468.

Gao, T., Han, Y., Yu, L., Ao, S., Li, Z. and Ji, J. (2014) CCNA2 is a prognostic biomarker for ER+ breast cancer and tamoxifen resistance. PLOS ONE, 9, 3.

Hsueh, H.M., Zhou, D.W., Tsai, C.A. (2013) Random forests-based differential analysis of gene sets for gene expression data. Gene, 518, 179-186.

Li, K.C. (1991) Sliced Inverse Regression for Dimension Reduction. Journal of the American Statistical Association, 86, 316-327.

Murphy, K.P. (2007) Conjugate bayesian analysis of the gaussian distribution. Technical report, University of British Columbia.

Riedel, K.S. (1991) A Sherman Morrison Woodbury identity for rank augmenting matrices with application to centering. SIAM J. MAT. ANAL., 12(1), 80-85.

Scha ̈fer, J. and Strimmer, K. (2005) A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics. Statistical Applications in Genetics and Molecular Biology, 4, 1.

Shao, Y. and Cook, R.D. and Weisberg, S. (2007) Marginal tests with sliced average variance estimation. Biometrika, 94, 285-296.

Singh, S.K., Grifson, J.J., Mavuduru, R.S., Agarwal, M.M., Mandal, A.K. and Jha, V. (2010) Serum leptin: a marker of prostate cancer irrespective of obesity. Cancer Biomarkers, 7, 11-15.

Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich, A., Pomeroy, S.L., Golub, T.R., Lander, E.S. and Mesirov, J.P. (2005) Gene set enrichment analysis：a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America, 102, 15545-15550.

Pang, H., Lin, A., Holford, M., Enerson, B.E., Lu, B., Lawton, M.P., Floyd, E. and Zhao, H. (2006) Pathway analysis using random forests classification and regression. Bioinformatics, 22, 2028-2036.

Terrasi, M., Riolfi, M., Ferla, R., Scolaro, L., Micciolo, R., Guidi, M. and Surmacz, E. (2009) Leptin and its receptor are overexpressed in brain tumors and correlate with the degree of malignancy. International Society of Neuropathology, 20(2), 481-489.
Tusher, V.G., Tibshirani, R. and Chu, G. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proceedings of the National Academy of Sciences of the United States of America, 98, 5116-5121.

Wang, X., Pyne, S. and Dinu, I. (2014) Gene set enrichment analysis for multiple continuous phenotypes. AIMSCS Research Report, No.: RR2014-05.

Wrann, C.D., Eguchi, J., Bozec, A., Xu, Z., Mikkelsen, T., Gimble, J., Nave, H., Wagner, E.F., Ong, S.E., Rosen, E.D. (2012) FOSL2 promotes leptin gene expression in human and mouse adipocytes. J Clin Invest, 122(3), 1010-1021.

Yan, X. and Sun, F. (2008) Testing gene set enrichment for subset of genes: Sub-GSE. BMC Bioinformatics, 9, 362.

Ye, C. and Eskin, E. (2007) Discovering tightly regulated and differentially expressed gene sets in whole genome expression data. Bioinformatics, 23 (2), 84-90.

徐碩亨、薛慧敏 (2013) Application of sufficient dimension reduction to global test.國立政治大學統計學系碩士論文，台北市。
描述 碩士
國立政治大學
統計研究所
101354015
102
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0101354015
資料類型 thesis
dc.contributor.advisor 薛慧敏zh_TW
dc.contributor.author (Authors) 蔡志旻zh_TW
dc.contributor.author (Authors) Tsai, Chih Minen_US
dc.creator (作者) 蔡志旻zh_TW
dc.creator (作者) Tsai, Chih Minen_US
dc.date (日期) 2013en_US
dc.date.accessioned 21-Jul-2014 15:36:41 (UTC+8)-
dc.date.available 21-Jul-2014 15:36:41 (UTC+8)-
dc.date.issued (上傳時間) 21-Jul-2014 15:36:41 (UTC+8)-
dc.identifier (Other Identifiers) G0101354015en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/67588-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 101354015zh_TW
dc.description (描述) 102zh_TW
dc.description.abstract (摘要) 生物現象多是由許多基因共同作用產生的結果，以基因組分析方法探討外顯特徵變數與基因組的相關性將更能幫助研究人員了解生物體的作用機制。目前已發展的基因組分析方法大多是針對離散型態的外顯特徵變數，在臨床醫學上，很多疾病的外顯特徵為連續型變數。本研究之目的即為發展運用在連續型外顯特徵變數的基因組分析方法。本文將考慮切片平均變異數估計法進行充分維度縮減的方法，原先被用來決定原始資料被縮減的程度之邊際維度檢定法將被運用於基因組分析方法。除了原有的邊際維度檢定法之外，我們另提出一改良的邊際維度檢定法，並以排列重抽法獲得這兩種檢定方法之排列顯著值。本文將透過電腦模擬以及實例分析來評估兩種邊際維度檢定法，同時也將列入Dinu等學者(2013)所發展的線性組合檢定法之結果以作為比較。zh_TW
dc.description.tableofcontents 摘要 ⅰ
目錄 ⅱ
第一章、緒論 1
第二章、分析方法 5
1.縮減維度和中央子空間 5
2.切片平均變異數估計 6
3.邊際維度檢定法 7
4.整體相關性檢定 8
5.改良型邊際維度檢定法 9
第三章、模擬分析 11
1.在虛無假設模型下 12
2.在對立假設模型下 14
第四章、實證分析 18
1.資料背景 18
2.分析結果 19
3.結果討論 24
第五章、結論與建議 26
參考文獻 28
附錄 32		zh_TW
dc.format.extent 1683507 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0101354015en_US
dc.subject (關鍵詞) 外顯特徵zh_TW
dc.subject (關鍵詞) 基因組分析zh_TW
dc.subject (關鍵詞) 切片平均變異數估計法zh_TW
dc.subject (關鍵詞) 邊際維度檢定法zh_TW
dc.title (題名) 運用充分資料縮減法於基因組分析zh_TW
dc.title (題名) Application of the Sufficient Dimension Reduction to Gene Set Analysisen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) Becker, C. and Gather, U. (2007) A note on the choice of the number of slices in sliced inverse regression. Technical Report, 475.

Biernacka, J.M., Geske, J., Jenkins, G.D., Colby, C., Rider, D.N., Karpyak, V.M., Choi, D. and Fridley, B.L. (2012) Genome-wide gene-set analysis for identification of pathways associated with alcohol dependence. International Journal of Neuropsychopharmacology, 16, 271-278.

Chang, S., Hursting, S.D., Contois, J.H., Strom, S.S., Yamamura, Y., Babaian, R.J., Troncoso, P., Scardino, P.T., Wheeler, T.M., Amos, C.I. and Spitz, M.R. (2001) Leptin and prostate cancer. The Prostate, 46, 62-67.

Chen, J., Pamuklar, Z., Spagnoli, A. and Torquati, A. (2012) Serum leptin levels are inversely correlated with omental gene expression of adiponectin and markedly decreased after gastric bypass surgery. Surg Endosc, 26, 1476-1480.

Cook, R.D. (1996) Graphics for regression with a binary response. Journal of the American Statistical Association, 91, 983-992.

Cook, R.D. and Lee, H. (1999) Dimension reduction in binary response regression. Journal of the American Statistical Association, 94, 1187-1200.
Cook, R.D. and Weisberg, S. (1991) Discussion of ”Sliced Inverse Regression for Dimension Reduction.” Journal of the American Statistical Association, 86, 328-332.

Dinu, I., Potter, J.D., Mueller, T., Liu, Q., Adewale, A.J., Jhangri, G.S., Einecke, G., Famulski, K.S., Halloran, P. and Yasui, Y. (2007) Improving gene set analysis of microarray data by SAM-GS. Bioinformatics, 8, 242.

Dinu, I., Wang, X., Kelemen, L.E., Vatanpour, S. and Pyne, S. (2013) Linear combination test for gene set analysis of a continuous phenotype. BMC Bioinformatics, 14, 212.

Eid, M.A., Kumar, M.V., Iczkowski, K.A., Bostwick, D.G. and Tindall, D.J. (1998) Expression of early growth response genes in human prostate cancer. Cancer Res, 58, 2461-2468.

Gao, T., Han, Y., Yu, L., Ao, S., Li, Z. and Ji, J. (2014) CCNA2 is a prognostic biomarker for ER+ breast cancer and tamoxifen resistance. PLOS ONE, 9, 3.

Hsueh, H.M., Zhou, D.W., Tsai, C.A. (2013) Random forests-based differential analysis of gene sets for gene expression data. Gene, 518, 179-186.

Li, K.C. (1991) Sliced Inverse Regression for Dimension Reduction. Journal of the American Statistical Association, 86, 316-327.

Murphy, K.P. (2007) Conjugate bayesian analysis of the gaussian distribution. Technical report, University of British Columbia.

Riedel, K.S. (1991) A Sherman Morrison Woodbury identity for rank augmenting matrices with application to centering. SIAM J. MAT. ANAL., 12(1), 80-85.

Scha ̈fer, J. and Strimmer, K. (2005) A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics. Statistical Applications in Genetics and Molecular Biology, 4, 1.

Shao, Y. and Cook, R.D. and Weisberg, S. (2007) Marginal tests with sliced average variance estimation. Biometrika, 94, 285-296.

Singh, S.K., Grifson, J.J., Mavuduru, R.S., Agarwal, M.M., Mandal, A.K. and Jha, V. (2010) Serum leptin: a marker of prostate cancer irrespective of obesity. Cancer Biomarkers, 7, 11-15.

Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich, A., Pomeroy, S.L., Golub, T.R., Lander, E.S. and Mesirov, J.P. (2005) Gene set enrichment analysis：a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America, 102, 15545-15550.

Pang, H., Lin, A., Holford, M., Enerson, B.E., Lu, B., Lawton, M.P., Floyd, E. and Zhao, H. (2006) Pathway analysis using random forests classification and regression. Bioinformatics, 22, 2028-2036.

Terrasi, M., Riolfi, M., Ferla, R., Scolaro, L., Micciolo, R., Guidi, M. and Surmacz, E. (2009) Leptin and its receptor are overexpressed in brain tumors and correlate with the degree of malignancy. International Society of Neuropathology, 20(2), 481-489.
Tusher, V.G., Tibshirani, R. and Chu, G. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proceedings of the National Academy of Sciences of the United States of America, 98, 5116-5121.

Wang, X., Pyne, S. and Dinu, I. (2014) Gene set enrichment analysis for multiple continuous phenotypes. AIMSCS Research Report, No.: RR2014-05.

Wrann, C.D., Eguchi, J., Bozec, A., Xu, Z., Mikkelsen, T., Gimble, J., Nave, H., Wagner, E.F., Ong, S.E., Rosen, E.D. (2012) FOSL2 promotes leptin gene expression in human and mouse adipocytes. J Clin Invest, 122(3), 1010-1021.

Yan, X. and Sun, F. (2008) Testing gene set enrichment for subset of genes: Sub-GSE. BMC Bioinformatics, 9, 362.

Ye, C. and Eskin, E. (2007) Discovering tightly regulated and differentially expressed gene sets in whole genome expression data. Bioinformatics, 23 (2), 84-90.

徐碩亨、薛慧敏 (2013) Application of sufficient dimension reduction to global test.國立政治大學統計學系碩士論文，台北市。		zh_TW