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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 莊曜宇(Eric Y. Chuang) | |
dc.contributor.author | Ying-Cheng Shen | en |
dc.contributor.author | 沈映成 | zh_TW |
dc.date.accessioned | 2022-11-25T07:31:12Z | - |
dc.date.available | 2023-08-31 | |
dc.date.copyright | 2021-10-23 | |
dc.date.issued | 2021 | |
dc.date.submitted | 2021-09-23 | |
dc.identifier.citation | 1. Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., Cho, J. H., Guttmacher, A. E., Kong, A., Kruglyak, L., Mardis, E., Rotimi, C. N., Slatkin, M., Valle, D., Whittemore, A. S., Boehnke, M., … Visscher, P. M. (2009). Finding the missing heritability of complex diseases. Nature, 461(7265), 747–753. https://doi.org/10.1038/nature08494 2. LaFramboise T. (2009). Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances. Nucleic acids research, 37(13), 4181–4193. https://doi.org/10.1093/nar/gkp552 3. Pierre, A. S., Genin, E. (2014). How important are rare variants in common disease? Briefings in Functional Genomics, 13(5), 353-361. doi:10.1093/bfgp/elu025 4. Li, Y., Willer, C., Sanna, S., Abecasis, G. (2009). Genotype imputation. Annual review of genomics and human genetics, 10, 387–406. https://doi.org/10.1146/annurev.genom.9.081307.164242 5. Marchini, J., Howie, B. (2010). Genotype imputation for genome-wide association studies. Nature Reviews Genetics, 11(7), 499-511. doi:10.1038/nrg2796 6. Higgins, J. P., White, I. R., Wood, A. M. (2008). Imputation methods for missing outcome data in meta-analysis of clinical trials. Clinical trials (London, England), 5(3), 225–239. https://doi.org/10.1177/1740774508091600 7. Davidovich, O., Halperin, E., Kimmel, G., Shamir, R. (2009). Increasing the power of association studies by imputation-based sparse tag SNP selection. Communications in Information and Systems, 9(3), 269-282. 8. 1000 Genomes Project Consortium, Auton, A., Brooks, L. D., Durbin, R. M., Garrison, E. P., Kang, H. M., Korbel, J. O., Marchini, J. L., McCarthy, S., McVean, G. A., Abecasis, G. R. (2015). A global reference for human genetic variation. Nature, 526(7571), 68–74. https://doi.org/10.1038/nature15393 9. International HapMap Consortium (2003). The International HapMap Project. Nature, 426(6968), 789–796. https://doi.org/10.1038/nature02168 10. McCarthy, S., Das, S., Kretzschmar, W., Delaneau, O., Wood, A. R., Teumer, A., Kang, H. M., Fuchsberger, C., Danecek, P., Sharp, K., Luo, Y., Sidore, C., Kwong, A., Timpson, N., Koskinen, S., Vrieze, S., Scott, L. J., Zhang, H., Mahajan, A., Veldink, J., … Haplotype Reference Consortium (2016). A reference panel of 64,976 haplotypes for genotype imputation. Nature genetics, 48(10), 1279–1283. https://doi.org/10.1038/ng.3643 11. NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium (2021). Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature, 590(7845), 290-299. https://doi.org/10.1038/s41586-021-03205-y 12. Deelen, P., Menelaou, A., van Leeuwen, E. M., Kanterakis, A., van Dijk, F., Medina-Gomez, C., Francioli, L. C., Hottenga, J. J., Karssen, L. C., Estrada, K., Kreiner-Møller, E., Rivadeneira, F., van Setten, J., Gutierrez-Achury, J., Westra, H. J., Franke, L., van Enckevort, D., Dijkstra, M., Byelas, H., van Duijn, C. M., … Swertz, M. A. (2014). Improved imputation quality of low-frequency and rare variants in European samples using the 'Genome of The Netherlands'. European journal of human genetics: EJHG, 22(11), 1321–1326. https://doi.org/10.1038/ejhg.2014.19 13. Panjwani, N., Xiao, B., Xu, L., Gong, J., Keenan, K., Lin, F., He, G., Baskurt, Z., Kim, S., Zhang, L., Esmaeili, M., Blackman, S., Scherer, S. W., Corvol, H., Drumm, M., Knowles, M., Cutting, G., Rommens, J. M., Sun, L., Strug, L. J. (2018). Improving imputation in disease-relevant regions: lessons from cystic fibrosis. NPJ genomic medicine, 3, 8. https://doi.org/10.1038/s41525-018-0047-6 14. Panjwani, N., Xiao, B., Xu, L., Gong, J., Keenan, K., Lin, F., He, G., Baskurt, Z., Kim, S., Zhang, L., Esmaeili, M., Blackman, S., Scherer, S. W., Corvol, H., Drumm, M., Knowles, M., Cutting, G., Rommens, J. M., Sun, L., Strug, L. J. (2018). Improving imputation in disease-relevant regions: lessons from cystic fibrosis. NPJ genomic medicine, 3, 8. https://doi.org/10.1038/s41525-018-0047-6 15. Dang, H., Gallins, P. J., Pace, R. G., Guo, X. L., Stonebraker, J. R., Corvol, H., Cutting, G. R., Drumm, M. L., Strug, L. J., Knowles, M. R., O'Neal, W. K. (2016). Novel variation at chr11p13 associated with cystic fibrosis lung disease severity. Human genome variation, 3, 16020. https://doi.org/10.1038/hgv.2016.20 16. Verma, S. S., Andrade, M. D., Tromp, G., Kuivaniemi, H., Pugh, E., Namjou-Khales, B., . . . Ritchie, M. D. (2014). Imputation and quality control steps for combining multiple genome-wide datasets. Frontiers in Genetics, 5. doi:10.3389/fgene.2014.00370 17. Das, S., Forer, L., Schönherr, S., Sidore, C., Locke, A. E., Kwong, A., Vrieze, S. I., Chew, E. Y., Levy, S., McGue, M., Schlessinger, D., Stambolian, D., Loh, P. R., Iacono, W. G., Swaroop, A., Scott, L. J., Cucca, F., Kronenberg, F., Boehnke, M., Abecasis, G. R., … Fuchsberger, C. (2016). Next-generation genotype imputation service and methods. Nature genetics, 48(10), 1284–1287. https://doi.org/10.1038/ng.3656 18. Loh, P. R., Danecek, P., Palamara, P. F., Fuchsberger, C., A Reshef, Y., K Finucane, H., Schoenherr, S., Forer, L., McCarthy, S., Abecasis, G. R., Durbin, R., L Price, A. (2016). Reference-based phasing using the Haplotype Reference Consortium panel. Nature genetics, 48(11), 1443–1448. https://doi.org/10.1038/ng.3679 19. Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., Abecasis, G. R. (2012). Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nature genetics, 44(8), 955–959. https://doi.org/10.1038/ng.2354 20. O'Connell, J., Gurdasani, D., Delaneau, O., Pirastu, N., Ulivi, S., Cocca, M., Traglia, M., Huang, J., Huffman, J. E., Rudan, I., McQuillan, R., Fraser, R. M., Campbell, H., Polasek, O., Asiki, G., Ekoru, K., Hayward, C., Wright, A. F., Vitart, V., Navarro, P., … Marchini, J. (2014). A general approach for haplotype phasing across the full spectrum of relatedness. PLoS genetics, 10(4), e1004234. https://doi.org/10.1371/journal.pgen.1004234 21. Howie, B. N., Donnelly, P., Marchini, J. (2009). A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS genetics, 5(6), e1000529. https://doi.org/10.1371/journal.pgen.1000529 22. Karki, R., Pandya, D., Elston, R. C., Ferlini, C. (2015). Defining 'mutation' and 'polymorphism' in the era of personal genomics. BMC medical genomics, 8, 37. https://doi.org/10.1186/s12920-015-0115-z 23. Shastry B. S. (2009). SNPs: impact on gene function and phenotype. Methods in molecular biology (Clifton, N.J.), 578, 3–22. https://doi.org/10.1007/978-1-60327-411-1_1 24. Meyer, O. S., Lunn, M., Garcia, S. L., Kjærbye, A. B., Morling, N., Børsting, C., Andersen, J. D. (2020). Association between brown eye colour in rs12913832:GG individuals and SNPs in TYR, TYRP1, and SLC24A4. PloS one, 15(9), e0239131. https://doi.org/10.1371/journal.pone.0239131 25. Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., Goddard, M. E., Visscher, P. M. (2010). Common SNPs explain a large proportion of the heritability for human height. Nature genetics, 42(7), 565–569. https://doi.org/10.1038/ng.608 26. Pang, G. S., Wang, J., Wang, Z., Lee, C. G. (2009). Predicting potentially functional SNPs in drug-response genes. Pharmacogenomics, 10(4), 639–653. https://doi.org/10.2217/pgs.09.12 27. Schlauch, K. A., Kulick, D., Subramanian, K., De Meirleir, K. L., Palotás, A., Lombardi, V. C. (2019). Single-nucleotide polymorphisms in a cohort of significantly obese women without cardiometabolic diseases. International journal of obesity (2005), 43(2), 253–262. https://doi.org/10.1038/s41366-018-0181-3 28. Al-Daghri, N. M., Al-Attas, O. S., Krishnaswamy, S., Mohammed, A. K., Alenad, A. M., Chrousos, G. P., Alokail, M. S. (2015). Association of Type 2 Diabetes Mellitus related SNP genotypes with altered serum adipokine levels and metabolic syndrome phenotypes. International journal of clinical and experimental medicine, 8(3), 4464–4471. 29. Gregersen, P. K., Olsson, L. M. (2009). Recent advances in the genetics of autoimmune disease. Annual review of immunology, 27, 363–391. https://doi.org/10.1146/annurev.immunol.021908.132653 30. Cross-Disorder Group of the Psychiatric Genomics Consortium, Lee, S. H., Ripke, S., Neale, B. M., Faraone, S. V., Purcell, S. M., Perlis, R. H., Mowry, B. J., Thapar, A., Goddard, M. E., Witte, J. S., Absher, D., Agartz, I., Akil, H., Amin, F., Andreassen, O. A., Anjorin, A., Anney, R., Anttila, V., Arking, D. E., … International Inflammatory Bowel Disease Genetics Consortium (IIBDGC) (2013). Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature genetics, 45(9), 984–994. https://doi.org/10.1038/ng.2711 31. Deng, N., Zhou, H., Fan, H., Yuan, Y. (2017). Single nucleotide polymorphisms and cancer susceptibility. Oncotarget, 8(66), 110635–110649. https://doi.org/10.18632/oncotarget.22372 32. Bisgin, A., Sonmezler, O., Boga, I., Yilmaz, M. (2021). The impact of rare and low-frequency genetic variants in common variable immunodeficiency (CVID). Scientific reports, 11(1), 8308. https://doi.org/10.1038/s41598-021-87898-1 33. Kent J. W., Jr (2011). Rare variants, common markers: synthetic association and beyond. Genetic epidemiology, 35 Suppl 1(Suppl 1), S80–S84. https://doi.org/10.1002/gepi.20655 34. Visscher, P. M., Brown, M. A., McCarthy, M. I., Yang, J. (2012). Five years of GWAS discovery. American journal of human genetics, 90(1), 7–24. https://doi.org/10.1016/j.ajhg.2011.11.029 35. Korte, A., Farlow, A. (2013). The advantages and limitations of trait analysis with GWAS: a review. Plant methods, 9, 29. https://doi.org/10.1186/1746-4811-9-29 36. Cai, M., Dai, S., Chen, W., Xia, C., Lu, L., Dai, S., Qi, J., Wang, M., Wang, M., Zhou, L., Lei, F., Zuo, T., Zeng, H., Zhao, X. (2017). Environmental factors, seven GWAS-identified susceptibility loci, and risk of gastric cancer and its precursors in a Chinese population. Cancer medicine, 6(3), 708–720. https://doi.org/10.1002/cam4.1038 37. Chagné, D., Crowhurst, R. N., Troggio, M., Davey, M. W., Gilmore, B., Lawley, C., Vanderzande, S., Hellens, R. P., Kumar, S., Cestaro, A., Velasco, R., Main, D., Rees, J. D., Iezzoni, A., Mockler, T., Wilhelm, L., Van de Weg, E., Gardiner, S. E., Bassil, N., Peace, C. (2012). Genome-wide SNP detection, validation, and development of an 8K SNP array for apple. PloS one, 7(2), e31745. https://doi.org/10.1371/journal.pone.0031745 38. Wang, H., Xu, X., Vieira, F. G., Xiao, Y., Li, Z., Wang, J., Nielsen, R., Chu, C. (2016). The Power of Inbreeding: NGS-Based GWAS of Rice Reveals Convergent Evolution during Rice Domestication. Molecular plant, 9(7), 975–985. https://doi.org/10.1016/j.molp.2016.04.018 39. Louhelainen J. (2016). SNP Arrays. Microarrays (Basel, Switzerland), 5(4), 27. https://doi.org/10.3390/microarrays5040027 40. Kumar, S., Banks, T. W., Cloutier, S. (2012). SNP Discovery through Next-Generation Sequencing and Its Applications. International journal of plant genomics, 2012, 831460. https://doi.org/10.1155/2012/831460 41. Peng, Z., Zhao, Z., Clevenger, J. P., Chu, Y., Paudel, D., Ozias-Akins, P., Wang, J. (2020). Comparison of SNP Calling Pipelines and NGS Platforms to Predict the Genomic Regions Harboring Candidate Genes for Nodulation in Cultivated Peanut. Frontiers in genetics, 11, 222. https://doi.org/10.3389/fgene.2020.00222 42. Roh, S. W., Abell, G. C., Kim, K. H., Nam, Y. D., Bae, J. W. (2010). Comparing microarrays and next-generation sequencing technologies for microbial ecology research. Trends in biotechnology, 28(6), 291–299. https://doi.org/10.1016/j.tibtech.2010.03.001 43. Marchini, J., Howie, B. (2010). Genotype imputation for genome-wide association studies. Nature reviews. Genetics, 11(7), 499–511. https://doi.org/10.1038/nrg2796 44. Quick, C., Anugu, P., Musani, S., Weiss, S. T., Burchard, E. G., White, M. J., Keys, K. L., Cucca, F., Sidore, C., Boehnke, M., Fuchsberger, C. (2020). Sequencing and imputation in GWAS: Cost-effective strategies to increase power and genomic coverage across diverse populations. Genetic epidemiology, 44(6), 537–549. https://doi.org/10.1002/gepi.22326 45. Huo, Y., Li, S., Liu, J., Li, X., Luo, X. J. (2019). Functional genomics reveal gene regulatory mechanisms underlying schizophrenia risk. Nature communications, 10(1), 670. https://doi.org/10.1038/s41467-019-08666-4 46. Naj A. C. (2019). Genotype Imputation in Genome-Wide Association Studies. Current protocols in human genetics, 102(1), e84. https://doi.org/10.1002/cphg.84 47. Chagnon, M., O'Loughlin, J., Engert, J. C., Karp, I., Sylvestre, M. P. (2018). Missing single nucleotide polymorphisms in Genetic Risk Scores: A simulation study. PloS one, 13(7), e0200630. https://doi.org/10.1371/journal.pone.0200630 48. Neale B. M. (2010). Introduction to linkage disequilibrium, the HapMap, and imputation. Cold Spring Harbor protocols, 2010(3), pdb.top74. https://doi.org/10.1101/pdb.top74 49. Stephens, M., Scheet, P. (2005). Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. American journal of human genetics, 76(3), 449–462. https://doi.org/10.1086/428594 50. Chattopadhyay, A., Lu, T. (2020). Overcoming the challenges of imputation of rare variants in a Taiwanese cohort. Translational Cancer Research, 9(7), 4065-4069. doi:10.21037/tcr-20-2395 51. Chou, W. C., Zheng, H. F., Cheng, C. H., Yan, H., Wang, L., Han, F., Richards, J. B., Karasik, D., Kiel, D. P., Hsu, Y. H. (2016). A combined reference panel from the 1000 Genomes and UK10K projects improved rare variant imputation in European and Chinese samples. Scientific reports, 6, 39313. https://doi.org/10.1038/srep39313 52. Sariya, S., Lee, J. H., Mayeux, R., Vardarajan, B. N., Reyes-Dumeyer, D., Manly, J. J., Brickman, A. M., Lantigua, R., Medrano, M., Jimenez-Velazquez, I. Z., Tosto, G. (2019). Rare Variants Imputation in Admixed Populations: Comparison Across Reference Panels and Bioinformatics Tools. Frontiers in genetics, 10, 239. https://doi.org/10.3389/fgene.2019.00239 53. Verma, S. S., de Andrade, M., Tromp, G., Kuivaniemi, H., Pugh, E., Namjou-Khales, B., Mukherjee, S., Jarvik, G. P., Kottyan, L. C., Burt, A., Bradford, Y., Armstrong, G. D., Derr, K., Crawford, D. C., Haines, J. L., Li, R., Crosslin, D., Ritchie, M. D. (2014). Imputation and quality control steps for combining multiple genome-wide datasets. Frontiers in genetics, 5, 370. https://doi.org/10.3389/fgene.2014.00370 54. Southam, L., Panoutsopoulou, K., Rayner, N. W., Chapman, K., Durrant, C., Ferreira, T., Arden, N., Carr, A., Deloukas, P., Doherty, M., Loughlin, J., McCaskie, A., Ollier, W. E., Ralston, S., Spector, T. D., Valdes, A. M., Wallis, G. A., Wilkinson, J. M., arcOGEN consortium, Marchini, J., … Zeggini, E. (2011). The effect of genome-wide association scan quality control on imputation outcome for common variants. European journal of human genetics : EJHG, 19(5), 610–614. https://doi.org/10.1038/ejhg.2010.242 55. Cai, C., Zhu, G., Zhang, T., Guo, W. (2017). High-density 80 K SNP array is a powerful tool for genotyping G. hirsutum accessions and genome analysis. BMC genomics, 18(1), 654. https://doi.org/10.1186/s12864-017-4062-2 56. Wagner M. J. (2013). Rare-variant genome-wide association studies: a new frontier in genetic analysis of complex traits. Pharmacogenomics, 14(4), 413–424. https://doi.org/10.2217/pgs.13.36 57. Chen, B., Cole, J. W., Grond-Ginsbach, C. (2017). Departure from Hardy Weinberg Equilibrium and Genotyping Error. Frontiers in genetics, 8, 167. https://doi.org/10.3389/fgene.2017.00167 58. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A., Bender, D., Maller, J., Sklar, P., de Bakker, P. I., Daly, M. J., Sham, P. C. (2007). PLINK: a tool set for whole-genome association and population-based linkage analyses. American journal of human genetics, 81(3), 559–575. https://doi.org/10.1086/519795 59. Nettelblad C. (2013). Breakdown of methods for phasing and imputation in the presence of double genotype sharing. PloS one, 8(3), e60354. https://doi.org/10.1371/journal.pone.0060354 60. International HapMap 3 Consortium, Altshuler, D. M., Gibbs, R. A., Peltonen, L., Altshuler, D. M., Gibbs, R. A., Peltonen, L., Dermitzakis, E., Schaffner, S. F., Yu, F., Peltonen, L., Dermitzakis, E., Bonnen, P. E., Altshuler, D. M., Gibbs, R. A., de Bakker, P. I., Deloukas, P., Gabriel, S. B., Gwilliam, R., Hunt, S., … McEwen, J. E. (2010). Integrating common and rare genetic variation in diverse human populations. Nature, 467(7311), 52–58. https://doi.org/10.1038/nature09298 61. Huang, J., Howie, B., McCarthy, S., Memari, Y., Walter, K., Min, J. L., Danecek, P., Malerba, G., Trabetti, E., Zheng, H. F., UK10K Consortium, Gambaro, G., Richards, J. B., Durbin, R., Timpson, N. J., Marchini, J., Soranzo, N. (2015). Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel. Nature communications, 6, 8111. https://doi.org/10.1038/ncomms9111 62. Choudhury, A., Hazelhurst, S., Meintjes, A., Achinike-Oduaran, O., Aron, S., Gamieldien, J., Jalali Sefid Dashti, M., Mulder, N., Tiffin, N., Ramsay, M. (2014). Population-specific common SNPs reflect demographic histories and highlight regions of genomic plasticity with functional relevance. BMC genomics, 15(1), 437. https://doi.org/10.1186/1471-2164-15-437 63. UK10K Consortium, Walter, K., Min, J. L., Huang, J., Crooks, L., Memari, Y., McCarthy, S., Perry, J. R., Xu, C., Futema, M., Lawson, D., Iotchkova, V., Schiffels, S., Hendricks, A. E., Danecek, P., Li, R., Floyd, J., Wain, L. V., Barroso, I., Humphries, S. E., … Soranzo, N. (2015). The UK10K project identifies rare variants in health and disease. Nature, 526(7571), 82–90. https://doi.org/10.1038/nature14962 64. Boomsma, D. I., Wijmenga, C., Slagboom, E. P., Swertz, M. A., Karssen, L. C., Abdellaoui, A., Ye, K., Guryev, V., Vermaat, M., van Dijk, F., Francioli, L. C., Hottenga, J. J., Laros, J. F., Li, Q., Li, Y., Cao, H., Chen, R., Du, Y., Li, N., Cao, S., … van Duijn, C. M. (2014). The Genome of the Netherlands: design, and project goals. European journal of human genetics: EJHG, 22(2), 221–227. https://doi.org/10.1038/ejhg.2013.118 65. Klein, C., Westenberger, A. (2012). Genetics of Parkinson's disease. Cold Spring Harbor perspectives in medicine, 2(1), a008888. https://doi.org/10.1101/cshperspect.a008888 66. Ngamphiw, C., Assawamakin, A., Xu, S., Shaw, P. J., Yang, J. O., Ghang, H., Bhak, J., Liu, E., Tongsima, S., HUGO Pan-Asian SNP Consortium (2011). PanSNPdb: the Pan-Asian SNP genotyping database. PloS one, 6(6), e21451. https://doi.org/10.1371/journal.pone.0021451 67. Mathias, R. A., Taub, M. A., Gignoux, C. R., Fu, W., Musharoff, S., O'Connor, T. D., Vergara, C., Torgerson, D. G., Pino-Yanes, M., Shringarpure, S. S., Huang, L., Rafaels, N., Boorgula, M. P., Johnston, H. R., Ortega, V. E., Levin, A. M., Song, W., Torres, R., Padhukasahasram, B., Eng, C., … Barnes, K. C. (2016). A continuum of admixture in the Western Hemisphere revealed by the African Diaspora genome. Nature communications, 7, 12522. https://doi.org/10.1038/ncomms12522 68. Shin, D. M., Hwang, M. Y., Kim, B. J., Ryu, K. H., Kim, Y. J. (2020). GEN2VCF: a converter for human genome imputation output format to VCF format. Genes genomics, 42(10), 1163–1168. https://doi.org/10.1007/s13258-020-00982-0 69. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., 1000 Genome Project Data Processing Subgroup (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics (Oxford, England), 25(16), 2078–2079. https://doi.org/10.1093/bioinformatics/btp352 70. Wei, C. Y., Yang, J. H., Yeh, E. C., Tsai, M. F., Kao, H. J., Lo, C. Z., Chang, L. P., Lin, W. J., Hsieh, F. J., Belsare, S., Bhaskar, A., Su, M. W., Lee, T. C., Lin, Y. L., Liu, F. T., Shen, C. Y., Li, L. H., Chen, C. H., Wall, J. D., Wu, J. Y., … Kwok, P. Y. (2021). Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese. NPJ genomic medicine, 6(1), 10. https://doi.org/10.1038/s41525-021-00178-9 71. Karczewski, K. J., Francioli, L. C., Tiao, G., Cummings, B. B., Alföldi, J., Wang, Q., Collins, R. L., Laricchia, K. M., Ganna, A., Birnbaum, D. P., Gauthier, L. D., Brand, H., Solomonson, M., Watts, N. A., Rhodes, D., Singer-Berk, M., England, E. M., Seaby, E. G., Kosmicki, J. A., Walters, R. K., … MacArthur, D. G. (2020). The mutational constraint spectrum quantified from variation in 141,456 humans. Nature, 581(7809), 434–443. https://doi.org/10.1038/s41586-020-2308-7 72. Kuhn, R. M., Haussler, D., Kent, W. J. (2013). The UCSC genome browser and associated tools. Briefings in bioinformatics, 14(2), 144–161. https://doi.org/10.1093/bib/bbs038 73. Juang, J. J., Lu, T. P., Su, M. W., Lin, C. W., Yang, J. H., Chu, H. W., Chen, C. H., Hsiao, Y. W., Lee, C. Y., Chiang, L. M., Yu, Q. Y., Hsiao, C. K., Chen, C. J., Wu, P. E., Pai, C. H., Chuang, E. Y., Shen, C. Y. (2020). Rare variants discovery by extensive whole-genome sequencing of the Han Chinese population in Taiwan: Applications to cardiovascular medicine. Journal of advanced research, 30, 147–158. https://doi.org/10.1016/j.jare.2020.12.003 74. Ma, P., Brøndum, R. F., Zhang, Q., Lund, M. S., Su, G. (2013). Comparison of different methods for imputing genome-wide marker genotypes in Swedish and Finnish Red Cattle. Journal of dairy science, 96(7), 4666–4677. https://doi.org/10.3168/jds.2012-6316 75. Delaneau, O., Zagury, J. F., Robinson, M. R., Marchini, J. L., Dermitzakis, E. T. (2019). Accurate, scalable and integrative haplotype estimation. Nature communications, 10(1), 5436. https://doi.org/10.1038/s41467-019-13225-y 76. Rubinacci, S., Delaneau, O., Marchini, J. (2020). Genotype imputation using the Positional Burrows Wheeler Transform. PLoS genetics, 16(11), e1009049. https://doi.org/10.1371/journal.pgen.1009049 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/82447 | - |
dc.description.abstract | "基因型插補(Genotype imputation),是在進行全基因組關聯研究(Genome wide association study ,GWAS)之前的重要步驟。它能透過龐大的參考序列資料庫進行預測並填補缺失的基因型以增加樣品的SNP密度和GWAS的分析資料性。然而,整個基因型插補過程包括一系列複雜的插補前以及插補後步驟,運算過程需要耗費龐大的運算資源量,並且也需要生物資訊學專業知識。因此,我們建立了一個對於使用者方便的網頁插補伺服器服務,名為Multi-racial Imputation System(MI-system),該服務分別使用生物資訊學家常用的pre-phasing 軟體SHAPEIT 和imputation軟體IMPUTE2進行運算。對於所使用的參考序列資料庫,該服務首次包括了Taiwan biobank(TWB)序列資料庫,並根據使用者需求為其提供1000 Genome Phase III和TWB以及Hapmap3序列資料庫可進行選擇,也添加了IMPUTE2特有的兩種merge reference imputation功能來增強插補的結果。該服務進一步提供了彈性的質量控制選項,並讓使用者能從多個選項中自行選擇所要篩選的次要等位基因頻率(Minor allele frequency)閾值、需要過濾的基因型及樣本缺失率以及Hardy-Weinberg平衡的閾值。為了增加使用者的便利性,該服務還提供了一些實用功能,例如(i)分割全基因組SNP資料,(ii)基因組座標軸轉換(grch37和grch38),以及(iii)透過使用者上傳的基因型資料建立定制建構參考序列資料庫。使用者只需要簡單的幾個步驟即可執行實用程式功能並快速獲得高通量的SNP插補資料。並能夠將結果轉換成與流行的GWAS分析工具(例如PLINK,SNPTest或R)兼容的格式進行下載,以方便進行後續分析。" | zh_TW |
dc.description.provenance | Made available in DSpace on 2022-11-25T07:31:12Z (GMT). No. of bitstreams: 1 U0001-0109202113565600.pdf: 8147333 bytes, checksum: 0e94a1892109df65d0fe4d1c3457c5b7 (MD5) Previous issue date: 2021 | en |
dc.description.tableofcontents | 誌謝 ii 中文摘要 iii Abstract iv Contents v List of figures vii List of tables ix Chapter 1 Introduction 1 1.1 Single Nucleotide Polymorphism (SNP) 4 1.2 Genome Wide Association Studies 5 1.3 SNP genotyping: Microarrays and Next generation sequencing 6 1.4 Genotype imputation 7 1.4.1. The introduction of genotype imputation 7 1.4.2 Genotype imputation of Rare variants 8 1.4.3 The steps of genotype imputation 9 1.5 Reference panel in genotype imputation 12 1.6 Imputation Server 14 1.7 Specific aim 15 Chapter 2 Materials and methods 17 2.1 System implementation 17 2.2 MI-System Reference Panels 18 2.3 MI-System: Services 19 2.3.1 Service 1: Imputation 20 2.3.2 Service 2: Create reference panel 24 2.3.3 Service 3: Split Chromosome 25 2.3.4 Service 4: Liftover 25 Chapter 3 Results 27 3.1 Web-interface: 27 3.2 Public reference panels 27 3.3 Service: Imputation 27 3.3.1 Improve the cost of imputation time 29 3.3.2 Comparison of MI-System with Michigan Imputation server. 29 3.3.3 Merge reference panels 32 3.3.4 Validate the imputation accuracy 33 3.4 Service: Split chromosome 34 3.5 Service: Liftover 35 3.6 Create reference 36 Chapter 4 Discussion 36 Chapter 5 Conclusions 39 Chapter 6 References 40 Appendix 53 Supplementary figure 79 | |
dc.language.iso | en | |
dc.title | 建構線上DNA變異位點插補伺服器 | zh_TW |
dc.title | Development of an online system for DNA imputation | en |
dc.date.schoolyear | 109-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 賴亮全(Hsin-Tsai Liu),蔡孟勳(Chih-Yang Tseng),盧子彬,郭錦輯 | |
dc.subject.keyword | 單核苷酸多態性,基因型插補, | zh_TW |
dc.subject.keyword | genotype imputation,single nucleotide polymorphism, | en |
dc.relation.page | 82 | |
dc.identifier.doi | 10.6342/NTU202102930 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2021-09-23 | |
dc.contributor.author-college | 生命科學院 | zh_TW |
dc.contributor.author-dept | 基因體與系統生物學學位學程 | zh_TW |
dc.date.embargo-lift | 2023-08-31 | - |
顯示於系所單位: | 基因體與系統生物學學位學程 |
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