home_precourse.Rmd

---
title: " "
output:
  bookdown::html_document2:
    toc: false
    number_sections: false
---

```{r,child="assets/header-lab.Rmd"}
```

```{r,eval=TRUE,include=FALSE}
library(yaml)
upid <- yaml::read_yaml("_site.yml")$uppmax_project
```

# Precourse {.tabset .tabset-fade}

These are absolutely necessary for the course, if you do not already have a working R environment with R studio:

<div class="instruction">
<i class="fas fa-exclamation-circle"></i> Download and install the latest version of R from [r-project.org](https://cloud.r-project.org/). Install Rtools from [https://cran.r-project.org/bin/](https://cran.r-project.org/bin/). Rtools may be needed for installing new packages from source. 

<i class="fas fa-exclamation-circle"></i> Install [RStudio](https://www.rstudio.com/products/rstudio/download/). RStudio provides you with tools like code editor with highlighting, project management, version control, package building, debugger, profiler and more.

<i class="fas fa-exclamation-circle"></i> install R packages necessary for this course:

```{r,eval=FALSE,block.title=TRUE}

install.packages(c("ggplot2","tidyverse","ggmap","pheatmap","devtools","cowplot",
                   "reshape2", "dplyr", "wesanderson", "scales", "ggthemes", "ggrepel",
                   "ggpubr", "gridExtra", "gganimate", "shiny", "rsconnect",
                   "grid", "shinythemes", "colourpicker"), dependencies = TRUE)

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install(c("ggtree", "treeio"))

```

<div class="boxy boxy-lightbulb">
<i class="fas fa-exclamation-circle"></i> To make sure that the installations went well, we will try to make a quick plot using the packages you just installed. In this plot, we try to see if there is correlation plot between `BMI` and average `no.of steps` taken by some volunteers per day. The data and the code for plotting is available [here](./data/Installation_check/packages_check.zip). Just `knit` the `Rmarkdown` file and you should see correlation the plot, if all the packages are installed properly. 

</div>

</div>

The following are the steps that are recommended for the course participants.

* Although you would have a small session on how to handle data in R, it is advisable for you to freshen up your memory on data-types such as `data.frame`, `matrix` and `read/write files` and so on. 

* Some warm-up exercises in R if you are interested can be found  [here](https://immuntech.github.io/Bioinformatics_Workshop_ImmTech/Data/2019-10-15/R_exercise_Lokesh.html)

* The data that is necessary for this course is available [here](https://nbisweden.github.io/workshop-data-visualization-r/2204/data/data.zip) and it is important to check that the `file-tree` looks OK.

# HackMD

https://hackmd.io/BcwXnvdVS469hIHXnDSvJg?both

***