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課程名稱 |
統計遺傳學原理暨基因體資料解讀
Principle of Statistical Genetics & Genome Data Interpretation |
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開課學期 |
111-2 |
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授課對象 |
醫學院 基因體暨蛋白體醫學研究所 |
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授課教師 |
許書睿 |
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課號 |
MolMed7019 |
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課程識別碼 |
448 M0380 |
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班次 |
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學分 |
2.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期五8,9(15:30~17:20) |
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上課地點 |
基醫508 |
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備註 |
分醫所碩士在職專班學生必修課.上課地點:醫學院未來教室(基醫508).與馮嬿臻合授
總人數上限：30人 |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
本課程為分子醫學研究所遺傳諮詢在職專班必修之統計課程，也歡迎有興趣的同學選修。透過一般授課課程、文獻導讀、個別口頭報告、以及小組報告的方式，讓每位同學都能具備解讀現代醫學基因體文獻的基礎知識以及遺傳諮詢所需的統計觀念。本課程將以文獻導讀方式，介紹美國醫學遺傳學暨基因體學學會(ACMG, American College of Medical Genetics and Genomics)與分子病理學學會(AMP, Association for Molecular Pathology AMP)所訂定之遺傳變異解讀準則，並加入臨床常見案例加以討論。
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課程目標 |
• 充分理解統計遺傳學原理並熟悉文獻中常見統計遺傳概念。
• 理解常見基因體檢測資料呈現方式，以及相關臨床應用
• 本課程著重於ACMG guidelines中統計相關資料的判讀。
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課程要求 |
個人口頭報告30%、分組口頭報告30%、作業與線上討論40%。
期中報告為個人報告，每個人針對一個名詞解釋，進行10分鐘報告。
期末報告為分組報告，每組針對課程大綱中重要文獻進行30-40分鐘報告。
口頭報告須“前一週” 週五下午14:20~15:10事先與授課老師討論報告內容。所有口頭報告評分方式皆包含同儕互評以及教師評分。 |
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預期每週課後學習時數 |
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Office Hours |
每週五 14:20~15:10 |
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指定閱讀 |
1. Sue R, Nazneen A, Sherri B, David B, Soma D, Julie G-F, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in Medicine. 2015;17(5):405-24.
2. Riggs ER, Andersen EF, Cherry AM, Kantarci S, Kearney H, Patel A, et al. Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen). Genet Med. 2020;22(2):245-57.
3. Gurdasani D, Barroso I, Zeggini E, Sandhu MS. Genomics of disease risk in globally diverse populations. Nature Reviews Genetics. 2019;20(9):520-35.
4. Sherman RM, Salzberg SL. Pan-genomics in the human genome era. Nature Reviews Genetics. 2020;21(4):243-54.
5. Zook JM, Hansen NF, Olson ND, Chapman L, Mullikin JC, Xiao C, et al. A robust benchmark for detection of germline large deletions and insertions. Nat Biotechnol. 2020;38(11):1347-55.
6. Torkamani A, Wineinger NE, Topol EJ. The personal and clinical utility of polygenic risk scores. Nature Reviews Genetics. 2018;19(9):581-90.
7. Timpson NJ, Greenwood CMT, Soranzo N, Lawson DJ, Richards JB. Genetic architecture: the shape of the genetic contribution to human traits and disease. Nature Reviews Genetics. 2018;19(2):110-24.
8. Povysil G, Petrovski S, Hostyk J, Aggarwal V, Allen AS, Goldstein DB. Rare-variant collapsing analyses for complex traits: guidelines and applications. Nature Reviews Genetics. 2019;20(12):747-59.
9. Zhang L, Bao Y, Riaz M, Tiller J, Liew D, Zhuang X, et al. Population genomic screening of all young adults in a health-care system: a cost-effectiveness analysis. Genetics in Medicine. 2019;21(9):1958-68.
10. Wei CY, Yang JH, Yeh EC, Tsai MF, Kao HJ, Lo CZ, et al. Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese. NPJ Genom Med. 2021;6(1):10.
建議延伸閱讀：
• Goldstein, D. B., et al. (2013). "Sequencing studies in human genetics: design and interpretation." Nature Reviews Genetics 14: 460.
• Sham, P. C. and S. M. Purcell (2014). "Statistical power and significance testing in large-scale genetic studies." Nature Reviews Genetics 15: 335.
• Speed, D. and D. J. Balding (2014). "Relatedness in the post-genomic era: is it still useful?" Nature Reviews Genetics 16: 33.
• Vermeesch, J. R., et al. (2016). "Prenatal and pre-implantation genetic diagnosis." Nature Reviews Genetics 17: 643.
• Rehm, H. L. (2017). "Evolving health care through personal genomics." Nature Reviews Genetics 18: 259.
• Payne, K., et al. (2018). "Cost-effectiveness analyses of genetic and genomic diagnostic tests. " Nature Reviews Genetics 19, 235-246.
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參考書目 |
• (Optional) Neale, B. M., M. A. Ferreira, S. E. Medland and D. Posthuma (2008).
Statistical genetics: gene mapping through linkage and association. New York ;
Taylor & Francis Group.
• Ramakrishna HK. (2017). Medical Statistics: for beginners
• Stram, D. O. (2014). Design, analysis, and interpretation of genome-wide
association scans. New York, NY, Springer New York.
• Datta, S. and D. Nettleton (2014). Statistical analysis of next generation
sequencing data / edited by Somnath Datta, Dan Nettleton. Cham, Springer
International Publishing. |
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
個人口頭報告 |
30% |
期中報告為個人報告，每個人針對一個名詞解釋，進行10分鐘報告。 |
2. |
分組口頭報告 |
30% |
期末報告為分組報告，每組針對課程大綱中重要文獻進行30-40分鐘報告。
口頭報告須“前一週” 週五下午14:20~15:10事先與授課老師討論報告內容。
所有口頭報告評分方式皆包含同儕互評以及教師評分。 |
3. |
作業與線上討論 |
40% |
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針對學生困難提供學生調整方式 |
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上課形式 |
提供學生彈性出席課程方式 |
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作業繳交方式 |
書面報告取代口頭報告, 學生與授課老師協議改以其他形式呈現 |
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考試形式 |
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其他 |
由師生雙方議定 |
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週次 |
日期 |
單元主題 |
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第1週 |
02/24 |
Introduction to Human Genome and Genotyping Methods |
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第2週 |
03/03 |
Basic Statistics for Genetic Counseling – Concepts of Biomedical Statistics |
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第3週 |
03/10 |
Basic Epidemiology for Genetic Counseling – Concepts of Genetic Epidemiology (Prevalence/Incidence rate/Relative Risk/Odds Ratio/Effect size) |
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第4週 |
03/17 |
Classical Genetics – Genotype Calling & ACMG Guidelines I (Benign/MAF/Pathogenic/VUS/IF59) (1) |
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第5週 |
03/24 |
Classical Genetics – Genotype Calling & ACMG Guidelines II (Benign/MAF/Pathogenic/VUS/IF59) (2) |
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第6週 |
03/31 |
Classical Genetics – Basic Genetics and Quantitative Genetics (Linkage/LE/LD/Heritability) |
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第7週 |
04/07 |
Classical Genetics – Basic Genetics and Inheritance Mode
(Mono,Oligo/AD/AR) |
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第8週 |
04/14 |
Classical Genetics – Relatedness and Population Genetics
(IBD/Population stratification/Founder effect, HW) (3) |
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第9週 |
04/21 |
Pharmacogenomics (Haplotype/Star * allele/Pseudogene) (4) |
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第10週 |
04/28 |
Benchmarking, Prediction Sensitivity/Specificity (5) |
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第11週 |
05/05 |
Genetics Architecture: Common diseases and Phenotypic Traits
(Polygenic/Pleiotropy) (6) |
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第12週 |
05/12 |
Polygenic risk score applications (7) (流預所馮嬿臻老師) |
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第13週 |
05/19 |
Genetics Architecture: Mendelian Disease and Rare Variants (8) |
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第14週 |
05/26 |
Cox Regression & Survival Analysis (9) |
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第15週 |
06/02 |
Genomics Data sharing and Biobanks I (10) |
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第16週 |
06/09 |
Genomics Data sharing and Biobanks II (TWB WGS) |
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