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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 生醫電子與資訊學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52732
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor莊曜宇(Dr. Eric Y. Chuang)
dc.contributor.authorZachariah James Pollocken
dc.contributor.author龐子瞻zh_TW
dc.date.accessioned2021-06-15T16:25:11Z-
dc.date.available2015-08-16
dc.date.copyright2015-08-16
dc.date.issued2015
dc.date.submitted2015-08-14
dc.identifier.citationReferences
1. Girirajan, Santhosh, Catarina D. Campbell, and Evan E. Eichler. “Human Copy Number Variation And Complex Genetic Disease.”Annual Review of Genetics Annu. Rev. Genet. 45.1 (2011): 203–226. Web.
2. Clancy, S. (2008) Copy number variation. Nature Education 1(1):95
3. Copy-number variation in control population cohorts - D. Pinto, C. Marshall, L. Feuk, S. Scherer. Human Molecular Genetics - 07/2007
4. Eichler, E. E. (2008) Copy Number Variation and Human Disease. Nature Education 1(3):1
5. Hastings, P. J. et al. “Mechanisms Of Change in Gene Copy Number.” Nat Rev Genet Nature Reviews Genetics10.8 (2009): 551–564. Web.
6. Charles P. Davis, MD, PhD (2014) http://www.medicinenet.com/esophageal_cancer/article.htm
8. Zhang Y. Epidemiology of esophageal cancer. World J Gastroenterol. 2013;19:5598–5606.
9. Denver Hendricks and M. Iqbal Parker (2008) Oesophageal Cancer in Africa. IUBMB Life
10. Tang, Yun-Chi, and Angelika Amon. “Gene Copy Number Alterations: A Cost-Benefit Analysis.” Cell. U.S. National Library of Medicine, n.d. Web. 4 Jun. 2015.
11. Jones L, Wei G, Sevcikova S, Phan V, Jain S, Shieh A, Wong JC, Li M, Dubansky J, Maunakea ML, Ochoa R, Zhu G, Tennant TR, Shannon KM, Lowe SW, Le Beau MM, Kogan SCJ. Gain of MYC underlies recurrent trisomy of the MYC chromosome in acute promyelocytic leukemia. Exp Med. 2010 Nov 22; 207(12):2581-94.
12. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3641674/
Tang, Yun-Chi, and Angelika Amon. “Gene Copy Number Alterations: A Cost-Benefit Analysis.” Cell. U.S. National Library of Medicine, n.d. Web. 4 Jun. 2015.

13. Sathirapongsasuti, J. F., H. Lee, B. A. Horst, G. Brunner, A. J. Cochran, S. Binder, J. Quackenbush, and S. F. Nelson (2011): “Exome Sequencing-Based Copy-Number Variation and Loss of Heterozygosity Detection: ExomeCNV.” Bioinformatics (Oxford, England)
14. All About The Human Genome Project (HGP).” All About The Human Genome Project (HGP). N.p., n.d. Web. 9 Jun. 2015.
15. Nucleic Acids Res. 2012 Nov 1;40(20):10073-83. doi: 10.1093/nar/gks666. Epub 2012 Sep 7.
16. “ATP Gene Family.” Genetics Home Reference. N.p., n.d. Web. 22 Jun. 2015. <http://ghr.nlm.nih.gov/genefamily/atp>
17. Ingenuity Systems, Redwood City, CA, USA; www.ingenuity.com

18. Expression of ATP2C1 in cancer - Summary - The Human Protein Atlas. N.p., n.d. Web. 22 Jun. 2015. <http://www.proteinatlas.org/ensg00000017260-atp2c1/cancer>
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52732-
dc.description.abstractABSTRACT
There is an immense amount of variability in the human genome that is caused by structural variation. Of these categories of variation in the genome, Copy Number Variation (CNV) is a prevalent form of structural variation where, when compared to a reference genome, alterations in the DNA give rise to a deviation in the number of copies of one or more multi-nucleotide segments of DNA.
These variations, dependent on the location, can affect gene expression and it has been suggested that CNV could play a significant role in the development of cancer. An over expression of an oncogene or under expression of a tumor suppressor gene could promote the development and occurrence rates of an associated cancer.
Esophageal squamous cell carcinoma (ESCC) is among the most common and deadliest cancers, ranking the eight most frequently diagnosed cancer globally and the sixth most in many asian countries(1). ESCC is a highly aggressive cancer, and due to its proclivity to metastasize and invade surrounding tissues, has a remarkably low survival rate.
This study investigates techniques of identifying Copy Number Variation in tumor normal pairs collected from patients with esophageal cancer, and uses these results to identify genes that are commonly associated with the disease. Our own custom method for CNV detection was developed and run alongside an established industry standard implementation.
Our method performed agreeably against our verification data as well as against the production tool on NGS data, reporting notably similar CNV locations per exon. Furthermore, we were able to identify a promising set of genes of interest by overlapping common CNVs per sample.
en
dc.description.provenanceMade available in DSpace on 2021-06-15T16:25:11Z (GMT). No. of bitstreams: 1
ntu-104-R02945044-1.pdf: 1073076 bytes, checksum: e4fc63fbe5eaa7d03d596657af480ca8 (MD5)
Previous issue date: 2015
en
dc.description.tableofcontentsCONTENTS
ACKNOWLEDGEMENTS…..…..……………………………………………………2
ABSTRACT..………………………………...………………………………………….5
Chapter 1 Introduction………………………………………………....…………..8
1.1 Copy Number Variation……………………………………………………………...8
1.2 Esophageal Cancer..…………………………………………………………….......11
1.3 Analysis of Copy Number Variation in Cancer…………………………………....12
1.3.1 Tumor Normal Pair Analysis………………………….……………………...13
1.4 Novel Tools vs. Existing tools………………………..……………………………...27
1.5 Existing CNV Detection Methods….……………………………………………….26
1.6 Novel CNV Detection Method….………………….…………...…………….…….27
1.7 Motivations and Goals……………………………………………………………….14
Chapter 2 Materials and Methods………………………………………………..15
2.1 Experiment Setup…………………………………...……………………………….15
2.2 Data Collection……………………………………………………………………....15
2.2.1 DNA Extraction……………………………………………………………...15
2.2.2 Sequencing………………………………………………………………..….16
2.3 Data Pre-processing…………………………………………………………….…...16
2.3.1 Alignment…………………………………………………………………….17
2.3.2 Indexing and File Manipulation ……………………………………………..17
2.3.3 Depth of coverage……………………………………………………....……18
2.4 Copy Number Variation Processing………………………………....……………..19
2.4.1 CNV Detection on Tumor Normal Pairs…………………………………...19
Chapter 3 Verification…………………………………………………………….21
3.1 Verification Data..……………………………………………………..……….……..22
3.1 Flux Simulator…….………………………………………………....…..……...……..22
3.2 Verification Data on Depth of Coverage………………………….……..…………...24
Chapter 4 CNV Method Comparison…………………………..…………….....26
4.1 Novel Tools vs. Existing tools on Verification Data…………….….…….…………...29
4.2 Novel Tools vs. Existing tools on Sample Data....…………………………………......30
4.3 Novel Tools vs. Existing tools on Speed…….......………………………………...…...31
Chapter 5 Results………………………………………………………………….33
5.1 Overview………………………………………………………………………….….34
5.2 Overlap of Exon Locations Containing Aberrations in Read Depth……………....35
5.3 Overlap of Genes Containing Aberrations in Read Depth………………………....36
5.4 Reduced Sample Set With Highest Common Overlap……………....………..38
5.5 Biological Pathways…………..……………………………………………..……….39
Chapter 6 Discussion……………………………………………………………...40
6.1 Choosing a Specificity………………………………………………………………41
6.2 Malformed Sample………………………………..……..………….……………….42
6.3 MIR InDels……………….…………………………………………….……..……….44
CONCLUSION…………..…..…..……………………………………………………46
References……………………………………………………………………………...45
Supplementary………………………………………………………………………...48
S.1 Top Genes of Interest from Overlapping Locations…………………………..…..48
S.2 Top Genes of Interest from Overlapping Locations on Reduced Set…….……..51
dc.language.isoen
dc.subject拷變數變異zh_TW
dc.subject深度覆蓋zh_TW
dc.subject食道癌zh_TW
dc.subject鱗狀細胞癌zh_TW
dc.subject外顯子組zh_TW
dc.subject次世代序列zh_TW
dc.subjectExomeen
dc.subjectEsophageal Canceren
dc.subjectNext Generation Sequencingen
dc.subjectSquamous Cell Carcinomaen
dc.subjectDepth of Coverageen
dc.subjectCopy Number Variationen
dc.title拷貝數變異對食道癌的分析zh_TW
dc.titleAnalysis of Copy Number Variation in Esophageal Canceren
dc.typeThesis
dc.date.schoolyear103-2
dc.description.degree碩士
dc.contributor.oralexamcommittee陳中平(Dr. Charlie Chung-Ping Chen),蔡孟勳(Tsai Mon-Hsun),盧子彬(Lu Tzu-Pin),賴亮全(Liang-Chuan Lai)
dc.subject.keyword拷變數變異,食道癌,次世代序列,鱗狀細胞癌,深度覆蓋,外顯子組,zh_TW
dc.subject.keywordCopy Number Variation,Esophageal Cancer,Next Generation Sequencing,Squamous Cell Carcinoma,Depth of Coverage,Exome,en
dc.relation.page46
dc.rights.note有償授權
dc.date.accepted2015-08-14
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept生醫電子與資訊學研究所zh_TW
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