**NBIS workshop with InfraVis on plotting with R**
# Data Visualization

Welcome to the *Workshop on plotting with R* organised by National Bioinformatics Infrastructure, Sweden.

This document is a life record of what we are doing and learning during the workshop. As either a student or a teacher, you are encouraged to write your comments, questions and feedback.


## Useful resources

- **Course website**: https://nbisweden.github.io/workshop-data-visualization-r/2505/
- **HackMD (this document):** https://hackmd.io/BcwXnvdVS469hIHXnDSvJg?both

# Beginners

- **Basic R**: https://immuntech.github.io/Bioinformatics_Workshop_ImmTech/Data/2019-10-15/R_exercise_Lokesh.html

## Data Download

## Introduction
Here, we write a few words about ourselves to get to know each other a bit better.

#### Teachers
* **Lokeshwaran Manoharan** - I am the course leader for this workshop. I work as a Bioinformatics expert at NBIS in the medical faculty node of Lund University. My research interest lies very much in the genomics of non-model organisms and microbes in particular.

* **Katja Kozjek** - I am a teacher for this workshop. I work as a bioinformatician at NBIS in the Medical faculty node of Lund University. I am mainly working with metagenomics data; soil, fungal, human microbiomes.

* **Massimiliano Volpe** - I am a teacher for this workshop. I work as a bioinformatician at NBIS in the Immunotechnology Department (Lund University). I work with transcriptomics, WGS and WES data.

#### Participants
* **Matteo Tomasini** - I am a research engineer in digital humanities at the Gothenburg Research Infrastructure in Digital Humanities (University of Gothenburg). I have used R extensively in my career, but never did much visualization with it beyond Base R. In my day-to-day I do mostly agent-based modelling in archaeology, and backend development and data analysis in several digital humanities projects.
* **Kostiantyn Kucher** - I am an associate professor in information visualization and visual analytics at Linköping University, Campus Norrköping, involved in the LiU node of InfraVis. I only have very basic introductory knowledge in R and I am using this course as an opportunity to learn and practice R as well as data processing and visualization libraries available in R, hopefully to be able to support collaborating domain experts who prefer R in their work in the future.

## Some important links

* [**Markdown syntax**](https://www.markdownguide.org/basic-syntax/)
* [**ggplot2 cheatsheet**](https://rstudio.github.io/cheatsheets/data-visualization.pdf)
* [**A really good and comprehensive R heatmap package**](https://jokergoo.github.io/ComplexHeatmap-reference/book/index.html) - Complex Heatmap
* [**R graph Gallery**](https://www.r-graph-gallery.com/)
* [**RShiny cheatsheet**](https://raw.githubusercontent.com/rstudio/cheatsheets/main/shiny.pdf)
* [**Statistics layers on ggplot2**](http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/76-add-p-values-and-significance-levels-to-ggplots/)

## Day 1

### Questions & Issues

- [ ] Example: **What does the parameter `by = 0` mean in `merged_data_wide <- merge(md, t(gc), by = 0)` ?**

> **Answer:** Here, the `merge` function will combine two data frames by their rownames, i.e., by invoking the parameter `by = 0`. Note that in the exercise, we have explicitly assigned the rownames of the dataframe by executing command `rownames(md) <- md$Sample_ID`.

### Bugs

### Feedback

## Day 2

### Questions & Issues

### Bugs

### Feedback

* Comments from Kostiantyn for both days: thank you for a great course! It has been very interesting and informative. The materials and presentations are all very well prepared, and it will be extremely helpful to come back to the materials after the course as well.