Genome Wide Association Studies Zhiwu Zhang Washington State University
Administration Why this course Overview Outline
No recording (video or audio) (link on the left) WeChat Administration
Label account with real name Use portrait starting from shoulders No politics and religions WeChat
Hosts: 25 Guests: 25 Online: ?
Teaching team Xiaolei Liu Guanghui HuJiabo WangMeijing LiangYou Tang
Thanks to organizers Shuhong ZhaoMei Yu
Beginners: Data process and tool selection Experienced: Method selection and result interpretation Advanced: Modeling and maximization of data values Developers: genetic models, statistical models, coding and software engineering Attendants
Mechanism of GWAS, pros and cons Experiment design: false discoveries, power and accuracy Analyses: methods and tools Reasoning and critical thinking Motivated through reinventing Objectives
Grade PercentageLetter 93%-100%A 90%-93%A- 87%-90%B+ 83%-87%B 80%-83%B- 77%-80%C+ 73%-77%C 70%-73%C- 66%-70%D+ 60%-66%D 0%-60%F Certificate
Participation Score No question, no discussion0% Question or discussion occasionally25% Question actively50% Discussion actively75% Question AND discussion actively100%
Assignments: five in total Due 5:00PM, Monday to Thursday Submit by PDF Report and R source code separately PDF report is limited to five pages. R source code should set seed for replicate of report No late submission accepted. Answers are given on next day Your homework may be selected for demonstration Homework
1.Hypotheses/statement 2.What did you observed (Results) 3.How to replicate your findings (Method) 4.Presentation: Description, figures and tables 5.R source code Homework components each takes 20%
Hypothesis (demo)
Result (demo)
Method (demo)
Presentation (demo)
007%2F Text book
Human genome Human genome 2 nd Generation Sequencing 2 nd Generation Sequencing
More Research on GWAS and GS By May 31, 2013
As fast as one season 50~300 kb resolution
Computing difficulties: millions of markers, individuals, and traits False positives, ex: “Amgen scientists tried to replicate 53 high-profile cancer research findings, but could only replicate 6”, Nature, 2012, 483: 531 False negatives Problems in GWAS
Associations on flowering time
2/3 of Statistical Genomics at WSU
Schedule Lecture SectionTitleRemark 17/4/16FundamentalSyllabus, introduction, and R (L01, L02) 27/4/16 Random variables and distribution (L03)HW1 37/5/16 Statistical inference (L04) 47/5/16 Linear algebra (L05)HW2 57/6/16 Genetic architecture and simulation of phenotype (L08) 67/6/16GWASMechanism of GWAS (L09, L10)HW3 77/7/16 Power, type I error and False Discovery Rate (L11) 87/7/16 General Linear Model (GLM) (L13)HW4 97/8/16 Structure and Kinship (L12, L14) 107/8/16 Mixed Linear Model (MLM) and Compression (L15, L16)HW5 117/9/16 SUPER GWAS method (L19) 127/9/16 FarmCPU (L21)Exam (L##: CROPS545 lecture number)
Morning: Theory Afternoon: Practice and homework Evening: Preparation Phases
Active participation + HWs + Exam GWAS: Very active for research and application Rapid development Highlight