請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99957完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 許書睿 | zh_TW |
| dc.contributor.advisor | Shu-Jui Hsu | en |
| dc.contributor.author | 李婕瑜 | zh_TW |
| dc.contributor.author | Chieh-Yu Lee | en |
| dc.date.accessioned | 2025-09-22T16:08:19Z | - |
| dc.date.available | 2025-09-23 | - |
| dc.date.copyright | 2025-09-22 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-08-06 | - |
| dc.identifier.citation | 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
Alkan, C., Coe, B. P., & Eichler, E. E. (2011). Genome structural variation discovery and genotyping. Nat Rev Genet, 12(5), 363-376. https://doi.org/10.1038/nrg2958 Babadi, M., Fu, J. M., Lee, S. K., Smirnov, A. N., Gauthier, L. D., Walker, M., Benjamin, D. I., Zhao, X., Karczewski, K. J., Wong, I., Collins, R. L., Sanchis-Juan, A., Brand, H., Banks, E., & Talkowski, M. E. (2023). GATK-gCNV enables the discovery of rare copy number variants from exome sequencing data. Nat Genet, 55(9), 1589-1597. https://doi.org/10.1038/s41588-023-01449-0 Behera, S., Catreux, S., Rossi, M., Truong, S., Huang, Z., Ruehle, M., Visvanath, A., Parnaby, G., Roddey, C., Onuchic, V., Finocchio, A., Cameron, D. L., English, A., Mehtalia, S., Han, J., Mehio, R., & Sedlazeck, F. J. (2024). Comprehensive genome analysis and variant detection at scale using DRAGEN. Nat Biotechnol. https://doi.org/10.1038/s41587-024-02382-1 Byrska-Bishop, M., Evani, U. S., Zhao, X., Basile, A. O., Abel, H. J., Regier, A. A., Corvelo, A., Clarke, W. E., Musunuri, R., Nagulapalli, K., Fairley, S., Runnels, A., Winterkorn, L., Lowy, E., Human Genome Structural Variation, C., Paul, F., Germer, S., Brand, H., Hall, I. M.,…Zody, M. C. (2022). High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios. Cell, 185(18), 3426-3440 e3419. https://doi.org/10.1016/j.cell.2022.08.004 Chen, X., Schulz-Trieglaff, O., Shaw, R., Barnes, B., Schlesinger, F., Kallberg, M., Cox, A. J., Kruglyak, S., & Saunders, C. T. (2016). Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics, 32(8), 1220-1222. https://doi.org/10.1093/bioinformatics/btv710 Collins, R. L., Brand, H., Karczewski, K. J., Zhao, X., Alfoldi, J., Francioli, L. C., Khera, A. V., Lowther, C., Gauthier, L. D., Wang, H., Watts, N. A., Solomonson, M., O'Donnell-Luria, A., Baumann, A., Munshi, R., Walker, M., Whelan, C. W., Huang, Y., Brookings, T.,…Talkowski, M. E. (2020). A structural variation reference for medical and population genetics. Nature, 581(7809), 444-451. https://doi.org/10.1038/s41586-020-2287-8 Collins, R. L., & Talkowski, M. E. (2025). Diversity and consequences of structural variation in the human genome. Nat Rev Genet. https://doi.org/10.1038/s41576-024-00808-9 Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., DePristo, M. A., Handsaker, R. E., Lunter, G., Marth, G. T., Sherry, S. T., McVean, G., Durbin, R., & Genomes Project Analysis, G. (2011). The variant call format and VCFtools. Bioinformatics, 27(15), 2156-2158. https://doi.org/10.1093/bioinformatics/btr330 Danecek, P., Bonfield, J. K., Liddle, J., Marshall, J., Ohan, V., Pollard, M. O., Whitwham, A., Keane, T., McCarthy, S. A., Davies, R. M., & Li, H. (2021). Twelve years of SAMtools and BCFtools. Gigascience, 10(2). https://doi.org/10.1093/gigascience/giab008 Duan, D. M., Cheng, C., Huang, Y. S., Chung, A. K., Chen, P. X., Chen, Y. A., Hsu, J. S., & Chen, P. L. (2025). Comparisons of performances of structural variants detection algorithms in solitary or combination strategy. PLoS One, 20(2), e0314982. https://doi.org/10.1371/journal.pone.0314982 Encode Project Consortium, Moore, J. E., Purcaro, M. J., Pratt, H. E., Epstein, C. B., Shoresh, N., Adrian, J., Kawli, T., Davis, C. A., Dobin, A., Kaul, R., Halow, J., Van Nostrand, E. L., Freese, P., Gorkin, D. U., Shen, Y., He, Y., Mackiewicz, M., Pauli-Behn, F.,…Weng, Z. (2020). Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature, 583(7818), 699-710. https://doi.org/10.1038/s41586-020-2493-4 English, A. C., Menon, V. K., Gibbs, R. A., Metcalf, G. A., & Sedlazeck, F. J. (2022). Truvari: refined structural variant comparison preserves allelic diversity. Genome Biol, 23(1), 271. https://doi.org/10.1186/s13059-022-02840-6 Escaramis, G., Docampo, E., & Rabionet, R. (2015). A decade of structural variants: description, history and methods to detect structural variation. Brief Funct Genomics, 14(5), 305-314. https://doi.org/10.1093/bfgp/elv014 Feng, Y. A., Chen, C. Y., Chen, T. T., Kuo, P. H., Hsu, Y. H., Yang, H. I., Chen, W. J., Su, M. W., Chu, H. W., Shen, C. Y., Ge, T., Huang, H., & Lin, Y. F. (2022). Taiwan Biobank: A rich biomedical research database of the Taiwanese population. Cell Genom, 2(11), 100197. https://doi.org/10.1016/j.xgen.2022.100197 Gardner, E. J., Lam, V. K., Harris, D. N., Chuang, N. T., Scott, E. C., Pittard, W. S., Mills, R. E., Genomes Project, C., & Devine, S. E. (2017). The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology. Genome Res, 27(11), 1916-1929. https://doi.org/10.1101/gr.218032.116 Heller, D., & Vingron, M. (2021). SVIM-asm: structural variant detection from haploid and diploid genome assemblies. Bioinformatics, 36(22-23), 5519-5521. https://doi.org/10.1093/bioinformatics/btaa1034 Hsu, J. S., Wu, D. C., Shih, S. H., Liu, J. F., Tsai, Y. C., Lee, T. L., Chen, W. A., Tseng, Y. H., Lo, Y. C., Lin, H. Y., Chen, Y. C., Chen, J. Y., Chou, T. H., Chang, D. T., Su, M. W., Guo, W. H., Mao, H. H., Chen, C. Y., & Chen, P. L. (2024). Complete genomic profiles of 1496 Taiwanese reveal curated medical insights. J Adv Res, 66, 197-207. https://doi.org/10.1016/j.jare.2023.12.018 Illumina. (2022). DRAGEN secondary analysis (Version 4.0) [Computer software]. https://www.illumina.com/products/by-type/informatics-products/dragen-secondary-analysis.html Jeffares, D. C., Jolly, C., Hoti, M., Speed, D., Shaw, L., Rallis, C., Balloux, F., Dessimoz, C., Bahler, J., & Sedlazeck, F. J. (2017). Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast. Nat Commun, 8, 14061. https://doi.org/10.1038/ncomms14061 Kosugi, S., Kamatani, Y., Harada, K., Tomizuka, K., Momozawa, Y., Morisaki, T., BioBank Japan, P., & Terao, C. (2023). Detection of trait-associated structural variations using short-read sequencing. Cell Genom, 3(6), 100328. https://doi.org/10.1016/j.xgen.2023.100328 Kosugi, S., Momozawa, Y., Liu, X., Terao, C., Kubo, M., & Kamatani, Y. (2019). Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing. Genome Biol, 20(1), 117. https://doi.org/10.1186/s13059-019-1720-5 Kronenberg, Z. N., Osborne, E. J., Cone, K. R., Kennedy, B. J., Domyan, E. T., Shapiro, M. D., Elde, N. C., & Yandell, M. (2015). Wham: Identifying Structural Variants of Biological Consequence. PLoS Comput Biol, 11(12), e1004572. https://doi.org/10.1371/journal.pcbi.1004572 Layer, R. M., Chiang, C., Quinlan, A. R., & Hall, I. M. (2014). LUMPY: a probabilistic framework for structural variant discovery. Genome Biol, 15(6), R84. https://doi.org/10.1186/gb-2014-15-6-r84 Li, H. (2018). Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics, 34(18), 3094-3100. https://doi.org/10.1093/bioinformatics/bty191 Li, H. (2021). New strategies to improve minimap2 alignment accuracy. Bioinformatics, 37(23), 4572-4574. https://doi.org/10.1093/bioinformatics/btab705 Liao, W. W., Asri, M., Ebler, J., Doerr, D., Haukness, M., Hickey, G., Lu, S., Lucas, J. K., Monlong, J., Abel, H. J., Buonaiuto, S., Chang, X. H., Cheng, H., Chu, J., Colonna, V., Eizenga, J. M., Feng, X., Fischer, C., Fulton, R. S.,…Paten, B. (2023). A draft human pangenome reference. Nature, 617(7960), 312-324. https://doi.org/10.1038/s41586-023-05896-x Mc Cartney, A. M., Shafin, K., Alonge, M., Bzikadze, A. V., Formenti, G., Fungtammasan, A., Howe, K., Jain, C., Koren, S., Logsdon, G. A., Miga, K. H., Mikheenko, A., Paten, B., Shumate, A., Soto, D. C., Sovic, I., Wood, J. M. D., Zook, J. M., Phillippy, A. M., & Rhie, A. (2022). Chasing perfection: validation and polishing strategies for telomere-to-telomere genome assemblies. Nat Methods, 19(6), 687-695. https://doi.org/10.1038/s41592-022-01440-3 McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R., Thormann, A., Flicek, P., & Cunningham, F. (2016). The Ensembl Variant Effect Predictor. Genome Biol, 17(1), 122. https://doi.org/10.1186/s13059-016-0974-4 Miller, D. T., Lee, K., Abul-Husn, N. S., Amendola, L. M., Brothers, K., Chung, W. K., Gollob, M. H., Gordon, A. S., Harrison, S. M., Hershberger, R. E., Klein, T. E., Richards, C. S., Stewart, D. R., Martin, C. L., & ACMG Secondary Findings Working Group. Electronic address: documents@acmg.net (2023). ACMG SF v3.2 list for reporting of secondary findings in clinical exome and genome sequencing: A policy statement of the American College of Medical Genetics and Genomics (ACMG). Genetics in medicine : official journal of the American College of Medical Genetics, 25(8), 100866. https://doi.org/10.1016/j.gim.2023.100866 Nancy F. Hansen, A. P., Sergey Koren, Brian Walenz. (2024). Telomere-to-telomere consortium HG002 "Q100" project. GitHub. https://github.com/marbl/hg002 Olson, N. D., Wagner, J., Dwarshuis, N., Miga, K. H., Sedlazeck, F. J., Salit, M., & Zook, J. M. (2023). Variant calling and benchmarking in an era of complete human genome sequences. Nat Rev Genet, 24(7), 464-483. https://doi.org/10.1038/s41576-023-00590-0 PacBio. (2024). pbmm2: A minimap2 frontend for PacBio native data formats (Version 1.14.99) [Computer software]. GitHub. https://github.com/PacificBiosciences/pbmm2/ PacBio. (2023). pbsv: PacBio structural variant (SV) calling and analysis tools (Version 2.9.0) [Computer software]. GitHub. https://github.com/PacificBiosciences/pbsv/ 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. Am J Hum Genet, 81(3), 559-575. https://doi.org/10.1086/519795 Rausch, T., Zichner, T., Schlattl, A., Stutz, A. M., Benes, V., & Korbel, J. O. (2012). DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics, 28(18), i333-i339. https://doi.org/10.1093/bioinformatics/bts378 Sudmant, P. H., Rausch, T., Gardner, E. J., Handsaker, R. E., Abyzov, A., Huddleston, J., Zhang, Y., Ye, K., Jun, G., Fritz, M. H., Konkel, M. K., Malhotra, A., Stutz, A. M., Shi, X., Casale, F. P., Chen, J., Hormozdiari, F., Dayama, G., Chen, K.,…Korbel, J. O. (2015). An integrated map of structural variation in 2,504 human genomes. Nature, 526(7571), 75-81. https://doi.org/10.1038/nature15394 Tan, J. H. J., Li, Z., Porta, M. G., Rajaby, R., Lim, W. K., Tan, Y. A., Jimenez, R. T., Teo, R., Hebrard, M., Ow, J. L., Ang, S., Jeyakani, J., Chong, Y. S., Lim, T. H., Goh, L. L., Tham, Y. C., Leong, K. P., Chin, C. W. L., Consortium, S. G. K. H.,…Bertin, N. (2024). A Catalogue of Structural Variation across Ancestrally Diverse Asian Genomes. Nat Commun, 15(1), 9507. https://doi.org/10.1038/s41467-024-53620-8 Van der Auwera, G. A., Carneiro, M. O., Hartl, C., Poplin, R., Del Angel, G., Levy-Moonshine, A., Jordan, T., Shakir, K., Roazen, D., Thibault, J., Banks, E., Garimella, K. V., Altshuler, D., Gabriel, S., & DePristo, M. A. (2013). From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr Protoc Bioinformatics, 43(1110), 11 10 11-11 10 33. https://doi.org/10.1002/0471250953.bi1110s43 Wala, J. A., Bandopadhayay, P., Greenwald, N. F., O'Rourke, R., Sharpe, T., Stewart, C., Schumacher, S., Li, Y., Weischenfeldt, J., Yao, X., Nusbaum, C., Campbell, P., Getz, G., Meyerson, M., Zhang, C. Z., Imielinski, M., & Beroukhim, R. (2018). SvABA: genome-wide detection of structural variants and indels by local assembly. Genome Res, 28(4), 581-591. https://doi.org/10.1101/gr.221028.117 Weischenfeldt, J., Symmons, O., Spitz, F., & Korbel, J. O. (2013). Phenotypic impact of genomic structural variation: insights from and for human disease. Nat Rev Genet, 14(2), 125-138. https://doi.org/10.1038/nrg3373 Westemeyer, M., Saucier, J., Wallace, J., Prins, S. A., Shetty, A., Malhotra, M., Demko, Z. P., Eng, C. M., Weckstein, L., Boostanfar, R., Rabinowitz, M., Benn, P., Keen-Kim, D., & Billings, P. (2020). Clinical experience with carrier screening in a general population: support for a comprehensive pan-ethnic approach. Genet Med, 22(8), 1320-1328. https://doi.org/10.1038/s41436-020-0807-4 Zhao, X., Emery, S. B., Myers, B., Kidd, J. M., & Mills, R. E. (2016). Resolving complex structural genomic rearrangements using a randomized approach. Genome Biol, 17(1), 126. https://doi.org/10.1186/s13059-016-0993-1 Zook, J. M., Hansen, N. F., Olson, N. D., Chapman, L., Mullikin, J. C., Xiao, C., Sherry, S., Koren, S., Phillippy, A. M., Boutros, P. C., Sahraeian, S. M. E., Huang, V., Rouette, A., Alexander, N., Mason, C. E., Hajirasouliha, I., Ricketts, C., Lee, J., Tearle, R.,…Salit, M. (2020). A robust benchmark for detection of germline large deletions and insertions. Nat Biotechnol, 38(11), 1347-1355. https://doi.org/10.1038/s41587-020-0538-8 | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99957 | - |
| dc.description.abstract | 結構變異 (structural variation, SV) 是指長度超過 50 個核苷酸的基因體遺傳變異。本研究利用美國國家標準與技術研究院 (National Institute of Standards and Technology, NIST) 轄下瓶中基因體 (Genome in a Bottle, GIAB) 聯盟釋出的結構變異基準資料集對多種定序技術和結構變異偵測流程進行評估。瓶中基因體聯盟的 0.6 版本結構變異基準資料集包含了標準樣本 HG002 生殖細胞系位於高信賴區域的 4,114 個大片段缺失以及 5,623 個大片段插入的序列資訊。為了更全面的評估結構變異偵測流程，本研究分別分析 HG002 及 40 個人類泛參考基因體聯盟 (Human Pangenome Reference Consortium, HPRC) 樣本的短讀長與長讀長全基因體定序資料，並相互驗證。針對長讀長全基因體定序資料，本研究使用序列比對 (alignment-based) 以及序列組裝 (assembly-based) 兩種方式分別比較結構變異偵測能力。針對短讀長全基因體定序資料，本研究整合了七個不同的偵測工具。評估結果顯示長讀長全基因體定序方式在偵測結構變異的方面表現優於短讀長。本研究結果也顯示，透過多種結構變異偵測工具整合，短讀長全基因體定序資料在不同族群檢體的表現相當一致。因此，本研究將分析流程運用到 1,480 位臺灣人體生物資料庫中短讀長全基因體定序資料的樣本上，總共偵測到了 90,578 個大片段缺失和 85,577 個大片段插入。其中有 85% 的結構變異為族群等位基因頻率小於 1% 的罕見變異，且大多數結構變異位於非編碼區。本研究利用千人基因體計劃樣本進行族群結構分析，確認結構變異的族群結構與單核苷酸變異的族群結構相似。本研究進一步估計疾病相關隱性遺傳基因上的結構變異攜帶者頻率，有 4.9% 的人帶有地中海型貧血基因 HBA1/HBA2 大片段缺失。 | zh_TW |
| dc.description.abstract | Structural variants (SVs) are genomic alterations spanning more than 50 nucleotides. We benchmarked SV detecting performance across multiple sequencing technologies and bioinformatics algorithms using expert-validated SV benchmark sets released by the Genome in a Bottle (GIAB) consortium (version 0.6). The benchmark set includes 4,114 large deletions and 5,623 insertions within the high-confidence regions of HG002, the son in an Ashkenazim Trio. To comprehensively evaluate SV detection methods, we analyzed short-read and long-read whole genome sequencing (WGS) data from HG002 and 40 samples from the Human Pangenome Reference Consortium (HPRC). For short-read WGS, we integrated results from seven short-read SV detection tools, including Delly, DRAGEN, GRIDSS, Lumpy, Manta, SvABA, and Wham as well as MELT for mobile element insertions (MEIs). For long-read WGS, we employed both alignment-based and assembly-based approaches. Benchmarking results demonstrated that long-read methods outperformed short-read methods. Our results indicate that the short-read SV detection workflow performed robustly across individuals from diverse populations. Our study applied this robust short-read SV detection workflow to 1,480 Taiwan Biobank (TWB) short-read WGS data and identified a total of 90,425 large deletions, 85,390 large insertions, and 11,434 MEIs. Notably, approximately 85% of SVs were rare variants and most located in non-coding regions. We estimated the alpha-thalassemia carrier frequency in the Taiwanese population to be about 5% based on the identified pathogenic deletions. Finally, we used the SV callsets from the 1000 Genomes Project to analyze population structure and confirmed that the population structure revealed by SVs was similar to that identified using single nucleotide variants (SNVs). | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-09-22T16:08:19Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-09-22T16:08:19Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 論文口試委員審定書 i
誌謝 ii 中文摘要 iii 英文摘要 iv 縮寫對照表 v 目次 vi 圖次 ix 表次 x Chapter 1 Introduction 1 1.1 The definition of structural variation (SV) 1 1.2 The algorithms of structural variant detection 1 1.3 Benchmarking structural variant detection 2 1.4 Population-scale SV catalogues in the world 3 1.5 The significance of establishing a Taiwanese SV catalogue 4 1.6 Research strategy and aims 5 Chapter 2 Materials and Methods 6 2.1 Data sources 6 2.1.1 Structural variant benchmark set 6 2.1.2 Reference samples for benchmarking 7 2.1.3 Study population 8 2.2 Structural variant detection 9 2.2.1 Large deletions and insertions 9 2.2.2 Mobile element insertions 9 2.3 Structural variant filtration and refinement 10 2.4 Integration of multiple SV callsets from diverse detection methods 12 2.5 Performance evaluation of SV detection methods 12 2.6 Structural variant annotation 13 2.6.1 Population allele frequency from gnomAD v4 SV dataset 13 2.6.2 Clinical significance from ClinVar database 15 2.6.2 Functional information based on ENCODE Registry of candidate cis-Regulatory Elements (cCREs) 15 2.7 Principal component analysis (PCA) for population stratification 16 2.7.1 TWB WGS cohort 16 2.7.2 Genetic similarity between TWB and 1000 Genomes Project phase 3 16 2.8 Fixation index (Fst) calculation for population similarity 18 2.9 Code availability and AI declaration 18 Chapter 3 Results 19 3.1 Benchmarking structural variants’ performance 19 3.1.1 Large deletions and insertions in HPRC release I 19 3.1.2 Long-read outperforms short-read methods on GIAB v0.6 SV benchmark 21 3.1.3 Short-read SV detection shows consistent performance across samples 22 3.2 Structural variant overview of 1,480 Taiwan Biobank samples 25 3.2.1 SV workflow robustness with siblings’ data 25 3.2.2 Comprehensive SV characterizations 26 3.2.3 Most SVs are rare and private to individuals 28 3.3 Functional analysis of the Taiwanese SVs 32 3.3.1 Most SVs are located on non-coding regions 32 3.3.2 Nearly 1.1% of participants carry potential actionable SVs 35 3.3.3 Nearly 4.9% of participants are alpha-thalassemia carriers 36 3.4 SV patterns of TWB and international cohorts 38 3.4.1 Taiwanese SVs demonstrate higher similarity to EAS than global populations 38 3.4.2 TWB lies genetically between CHB and CHS populations 40 Chapter 4 Discussion 49 Reference 54 附錄 60 | - |
| dc.language.iso | en | - |
| dc.subject | 工具比較 | zh_TW |
| dc.subject | 結構變異 | zh_TW |
| dc.subject | 族群結構 | zh_TW |
| dc.subject | 生物資訊學 | zh_TW |
| dc.subject | bioinformatics | en |
| dc.subject | population structure | en |
| dc.subject | benchmarking | en |
| dc.subject | structure variation | en |
| dc.title | 臺灣人體生物資料庫全基因體定序資料集之基因體結構變異特徵分析 | zh_TW |
| dc.title | Genomic Structural Variation Characterization of the Taiwan Biobank Whole Genome Sequencing Cohort | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 陳沛隆;陳倩瑜;陳弘昕 | zh_TW |
| dc.contributor.oralexamcommittee | Pei-Lung Chen;Chien-Yu Chen;Hung-Hsin Chen | en |
| dc.subject.keyword | 結構變異,工具比較,生物資訊學,族群結構, | zh_TW |
| dc.subject.keyword | structure variation,benchmarking,bioinformatics,population structure, | en |
| dc.relation.page | 60 | - |
| dc.identifier.doi | 10.6342/NTU202504136 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2025-08-07 | - |
| dc.contributor.author-college | 醫學院 | - |
| dc.contributor.author-dept | 基因體暨蛋白體醫學研究所 | - |
| dc.date.embargo-lift | 2027-07-31 | - |
| 顯示於系所單位： | 基因體暨蛋白體醫學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-113-2.pdf 未授權公開取用 | 9.63 MB | Adobe PDF | 檢視/開啟 |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。