Overview of course

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# Overview of course
## APSC 5984/20816 Complex Trait Genomics
### Gota Morota
### 1/22/2020

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# Holidays
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# 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

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# About the course
- [http://morotalab.org/apsc5984-2020/APSC5984.html](http://morotalab.org/apsc5984-2020/APSC5984.html)
- hands-on analysis of simulated or real genomic data
- no mideterm exams
- final exam 
- biweekly assignments
- 15-30 minutes presentation 
- R + RStudio

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# Reproducible Research
<iframe width="1000" height="500" src="https://www.youtube.com/embed/j7K3s_vi_1Y" frameborder="0" allowfullscreen></iframe>

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# 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

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# 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.

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# CRAN Task View: Reproducible Research
 [https://cran.r-project.org/web/views/ReproducibleResearch.html](https://cran.r-project.org/web/views/ReproducibleResearch.html)

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# 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

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# Bibliography
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# 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/)