DataAnalysis4LifeSciencesHD

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DataAnalysis4LifeSciencesHD

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Course Data Analysis for Life Sciences based on the material by Rafael Irizarry & Mike Love

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# Data Analysis for Life Sciences 
This repository contains the material for the course on Data Analysis for Life Sciences taught as a virtual class by [Wolfgang Huber](https://www.huber.embl.de) and [Britta Velten](https://github.com/bv2) at Heidelberg university in the summer semester 2020. The course is mainly based on the material by Rafael Irizarry, Mike Love and further contributors that was assembled at their [webpage](https://rafalab.github.io/pages/harvardx.html).

## Literature
The course mainly follows the chapters of the book *Data Analysis for Life Science* by Rafael Irizarry and Mike Love. A free pdf version can be obtained [here](https://leanpub.com/dataanalysisforthelifesciences). (You can move the slider to 0$ to get a free copy). In the pdf version you will find links to Rmd-Documents that were used to generate the book and can be used to directly re-run and experiment with the code.

## Course agenda
The course consists of 13 days plus a personal data analysis project, where each day covers parts of the book *Data Analysis for Life Science*, accompanied by YouTube lectures of the authors and exercises to be solved. Please click on the respective day to go to the material relevant for each day.

* [Day 1 (18/05)](material/day1/) :  Getting started with R and GitHub and basic data wrangling
* [Day 2 (19/05)](material/day2/) : Probability theory I: Random variables, central limit theorem and t-tests 
* [Day 3 (20/05)](material/day3/) : Probability theory II: Inference
* [Day 4 (22/05)](material/day4/) : Exploratory Data Analysis and Robust Statistics
* [Day 5 (25/05)](material/day5/) : Matrices and matrix algebra
* [Day 6 (26/05)](material/day6/) : Linear Models
* [Day 7 (27/05)](material/day7/) : **Exercises**: Wrap-up and further practice on Day 1 - Day 6
* [Day 8 (28/05)](material/day8/) : Multiple testing
* [Day 9 (29/05)](material/day9/) : Statistical Models and Bayesian Analysis 
* [Day 10 (02/06)](material/day10/) : RNAseq analysis
* [Day 11 (03/06)](material/day11/) : **Exercises**:  Wrap-up and further practice on  RNAseq analysis
* Day 12 (04/06): Project
* Day 13 (05/06) : Project

## Optional material

* [Dimension reduction](material/optional/SVD)
* [Clustering](material/optional/clustering)
* [Machine Learning](material/optional/ML)
* [Batch effects](material/optional/batcheffects)

## Course Slack channel
All discussions, announcemnets and Q&A sessions of the course will be communicaed via a [Slack](https://slack.com) channel. This is also a place to discuss and exchange among participants. In case you are not yet in the Slack channel, please write an e-mail to Britta Velten `b.velten@dkfz-heidelberg.de`.

## Q&A Sessions
Q&A Sessions will take place via Zoom every Monday and Thursday at 10am (duration: 30min - 1 hour). Details will be announced via Slack.
**Note: The last Q&A session on June 4 will start at 10:30am**

The first Q&A session on Monday May 18 will serve as an introduction to the course explaining:

- how to use the course material (book, lectures, scripts and git repository)
- how to hand in exercises
- how Q&A sessions will work
- how the Slack channel should be used
- the criteria for course evaluation

In the following Q&A sessions we will answer your questions on the course and discuss solutions to the wrap-up exercises. Please post any questions in the  [#questions channel](https://dataanalysis4-xqg7747.slack.com/archives/C012RP3781H) in Slack and we will answer them directly or in the following Q&A session.

## Exercises and course evaluation
On two days (Day 7 and Day 11) there will be no new material. Instead on these days you will go through an exercise that repeats the concepts from the previous days. To pass the course please hand in these exercises. For this, please upload the .Rmd file(s) and .html report(s) containing your solutions to a [personal slack conversation with Britta Velten](https://dataanalysis4-xqg7747.slack.com/archives/D012Q4UHDGV) by the evening of the day *before the next Q&A session*. The course will be evaluated on basis of a data analysis project (see below). How to generate the .html file and use RMarkdown (.Rmd) files will be explained on Day 1.

For the evaluation of the course you are supposed to conduct a small personal data analysis project where you can use the concepts and tools that you have learnt during the course. For this you will have time on the last two days of the course. This project should be handed in by Friday evening (June 5) as an .html report and will be graded.

DataAnalysis4LifeSciencesHD

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