class: center, middle, inverse, title-slide # Overview of course ## ASCI 944 / STAT 844 ### Gota Morota ### 2018/01/9 --- # <div align="center"> <img src="miami.jpg"> </div> --- # Statistical analysis of quantitative genetics What we will cover - genomic relationships - genomic selection - genome-enabled prediction - additive and non-additive effects - genome-wide association study - genomic heritability - statistical genomics of disease - population stratification - multiple-trait model - causal inference --- # About the course - [http://morotalab.org/asci944-2018/ASCI944.html](http://morotalab.org/asci944-2018/ASCI944.html) - hands-on analysis of simulated or real genomic data - no mideterm exams - final exam - 15 minutes presentation - R + RStudio --- # Prediction vs. Inference - 1 - Complex traits - large number of genes with small effects - genetics and environments - Inference - effect of allele substitution - variance component estimation - Prediction - prediction of yet-to-be observed phenotypes - genomic selection --- # Prediction vs. Inference - 2 <div align="center"> <img src="Lo2015PNAS.png" width=900 height=400> </div> * [http://www.pnas.org/content/112/45/13892.abstract ](http://www.pnas.org/content/112/45/13892.abstract ) --- # Reproducible Research <iframe width="1000" height="500" src="https://www.youtube.com/embed/j7K3s_vi_1Y" frameborder="0" allowfullscreen></iframe> --- # Reproducible research Many scientific journals now require authors to make their **data** publicly available prior to publication. - [Genetics](http://genetics.org/) - [Genome Research](http://genome.cshlp.org/) - [Heredity](http://www.nature.com/hdy/index.html) - [PLoS Genetics](http://journals.plos.org/plosgenetics/) and more. Some journals also encourage authors to share their **software or code** used for analysis --- # Reproducible research tools Examples - README file - GNU make - Git/GitHub - Jupyter Notebook - [R markdown](http://rmarkdown.rstudio.com/) + [knitr](https://yihui.name/knitr/) Submit .**Rmd** and .**html** files. --- # CRAN Task View: Reproducible Research [https://cran.r-project.org/web/views/ReproducibleResearch.html](https://cran.r-project.org/web/views/ReproducibleResearch.html) --- # Homework assignments Grading policies - reproducible data analysis - documentation of code - interpretation of results I encourage you to discuss with people in the class but **do not** share code --- # Bibliography <div align="center"> <img src="books.png" width=700 height=500> </div> --- # Online R Tutorials - [Code School: Try R](http://tryr.codeschool.com) - [Rabbit: Introduction to R](http://www.quantide.com/rabbit-introduction-to-r/) - [swirl](http://swirlstats.com/) - [statsTeachR](http://www.statsteachr.org/) - [The R Inferno](http://www.burns-stat.com/documents/books/the-r-inferno/) - [An Introduction to Statistical and Data Sciences via R](https://ismayc.github.io/moderndiver-book/) Useful cheat sheets - [RStudio Cheat Sheets](https://www.rstudio.com/resources/cheatsheets/)