index.Rmd

---
title: "Omics Data Analysis"
author: "Laurent Gatto"
date: "`r Sys.Date()`"
site: bookdown::bookdown_site
knit: bookdown::preview_chapter
description: "Course material for the Omics Data Analysis (WSBIM2122) course at UCLouvain."
output:
  msmbstyle::msmb_html_book:
    toc: TRUE
    toc_depth: 1
    split_by: chapter
    split_bib: no
    css: style.css
link-citations: yes
bibliography: [refs.bib, packages.bib]
---

# Preamble {-}

The [WSBIM2122](https://uclouvain.be/cours-2021-wsbim2122.html) course
is a project-based course that teaches the analysis of quantitative
omics data. It is composed of three major parts:

- Introductory material about the command line interface, advanced
  usage of R markdown for reports and slides, linear models, and
  utilisation and interpretation of gene set enrichment and
  over-representation analyses (GSEA).

- Project 1: analysis and interpretation of RNA-Seq data, including
  high throughput sequencing (HTS) data processing.

- Project 2: analysis and interpretation of quantitative proteomics,
  including mass spectrometry data (MS) and its processing.

Each project will entail an introductory lecture, dedicated office
time for students to ask questions, oral presentations of the data
analysis and interpretation, and submission of a fully reproducible R
markdown report. The students will be able to amend their final
reports after the presentations, benefiting from the in-class
feedback and discussion. The report will contain an introduction, a
description of the experimental design of the data, a detailed
description of the data analysis steps, discussion and interpretation
of the results, including a biological interpretation, as well as
references and contribution statement of all authors.

The projects will be done in groups, with different groups for each
project. The number of students per group will be set once the total
number of students is known.

Tentative schedule for the course.

- Shell and Rmd
- Linear models
- Project 1: lecture on HTS, RNA-Seq and
- Project 1 (cont'd): Gene set enrichment
- QA session for project 1
- Project 1 presentations
- Submission of the 1st report
- Project 2: lecture on MS and quantitative proteomics
- QA session for project 2
- Project 2 presentations
- Submission of the 2nd report
- Oral exams based on the submitted reports.

The course will be taught in English. The reports and oral exams can
be either in English or in French. The final mark will be based on the
submitted reports and the oral exam, tentatively about 50% each.


## Pre-requisites {-}

Students taking this course should be comfortable with data analysis
and visualisation in R. Formal pre-requisites for students taking the
class are the [WSBIM1207](https://UCLouvain-CBIO.github.io/WSBIM1207)
and [WSBIM1322](https://UCLouvain-CBIO.github.io/WSBIM1322).

Software requirements are documented in the *Setup* section below.

## About this course material {-}

This material is written in R markdown [@R-rmarkdown] and compiled as a
book using `knitr` [@R-knitr] `bookdown` [@R-bookdown]. The source
code is publicly available in a Github repository
[https://github.com/uclouvain-cbio/WSBIM2122](https://github.com/uclouvain-cbio/WSBIM2122)
and the compiled material can be read at http://bit.ly/WSBIM2122.

Contributions to this material are welcome. The best way to contribute
or contact the maintainers is by means of pull requests and
[issues](https://github.com/uclouvain-cbio/WSBIM2122/issues). Please
familiarise yourself with the [code of
conduct](https://github.com/UCLouvain-CBIO/WSBIM2122/blob/master/CONDUCT.md). By
participating in this project you agree to abide by its terms.

## Citation {-}

If you use this course, please cite it as

> Laurent Gatto and Axelle Loriot. *UCLouvain-CBIO/WSBIM2122: Omics
> data analysis.* https://github.com/UCLouvain-CBIO/WSBIM2122.


## License {-}

This material is licensed under the [Creative Commons
Attribution-ShareAlike 4.0
License](https://creativecommons.org/licenses/by-sa/4.0/).


## Setup {-}

We will be using the [R environment for statistical
computing](https://www.r-project.org/) as main data science language.
We will also use the
[RStudio](https://www.rstudio.com/products/RStudio/) interface to
interact with R and write scripts and reports. Both R and RStudio are
easy to install and works on all major operating systems.

Once R and RStudio are installed, a set of packages will need to be
installed. See section \@ref(sec-setup2) for details.

The `rWSBIM2122` package provides some pre-formatted data used in this
course. It can be installed with

```{r, eval = FALSE}
BiocManager::install("UCLouvain-CBIO/rWSBIM2122")
```

and then loaded with

```{r rwsbim1322, message = FALSE, warning = FALSE}
library("rWSBIM2122")
```

To build this book, you'll need `bookdown` [@R-bookdown] and a
fork[^msmbfork] of [`msmbstyle`
style](https://github.com/grimbough/msmbstyle/) [@R-msmbstyle].

[^msmbfork]: https://github.com/lgatto/msmbstyle

```{r combilebook1, eval=FALSE}
install.packages("bookdown")
devtools::install_github("lgatto/msmbstyle")
```

In the course's work directory, simply type

```{r combilebook2, eval=FALSE}
bookdown::render_book(".")
```