---
title: "Welcome to Big Data Biology (BIO00047I)"
author: ""
output:
  html_document:
    depth: 3
    theme: spacelab
    toc: yes
    toc_float:
      collapsed: no
      smooth_scroll: no
  pdf_document:
    toc: yes
  word_document: default
editor_options: 
  chunk_output_type: console
---

**Quick links:**
[Videos](http://www-users.york.ac.uk/~dj757/BIO00047I/videos.html) | [Workshops](https://www-users.york.ac.uk/~dj757/BIO00047I/workshops.html) | [Module synopsis](https://www.york.ac.uk/students/studying/manage/programmes/module-catalogue/module/BIO00047I/latest) |  [VLE Site](https://vle.york.ac.uk/webapps/blackboard/execute/content/blankPage?cmd=view&content_id=_3572727_1&course_id=_96760_1) | [List of staff](https://vle.york.ac.uk/webapps/blackboard/execute/staffinfo/manageStaffInfo?course_id=_99703_1&mode=view&mode=cpview) | [The data](http://www-users.york.ac.uk/~dj757/BIO00047I/misc/BIO00047I-data-description-2021.pdf) | [Report Guide ](http://www-users.york.ac.uk/~dj757/BIO00047I/misc/BIO00047I-report-guide-and-marking-scheme-2022.pdf) 


***

![](pics/array.png)

#Intro
This module will teach you how to analyse large biological data sets. We use R Studio as a tool, but this is not a module about R Studio. We use statistical tests, but this is not a module about statistics. **This module is about using large tables of data to understand biology.** Keep your eyes open, you may see something wonderful. We hope so.

The formal Module synopsis and learning outcomes are [here ](https://www.york.ac.uk/students/studying/manage/programmes/module-catalogue/module/BIO00047I/latest).

#How this module works (what you need to do)
* **Attend the  workshops**. We have five workshops this term. Attend them all. In these workshops we will teach you how to do data analysis.

* **Data sets:** we have four data sets, and exercises for each. You should choose **two** that you like, and work though the exercises during the workshops. Choose **one* of these two write your report on.

* **Watch some data analysis and R skills videos**. All the videos are here. A list of the order that we suggest watching them in is in the [week by week guide](https://vle.york.ac.uk/webapps/blackboard/execute/content/blankPage?cmd=view&content_id=_3999746_1&course_id=_99703_1) in the VLE.


* **Assessement:** Do some analysis using **one** of the data sets we provide and write a 1500 word report about it.

* Hand the report in before **Thursday 21st of April 2022 at 11am**.

***

#Week by week guide
See the VLE for the [week by week guide](https://vle.york.ac.uk/webapps/blackboard/execute/content/blankPage?cmd=view&content_id=_3999746_1&course_id=_99703_1) of what to do.


***

#Videos 
All the videos are [here](http://www-users.york.ac.uk/~dj757/BIO00047I/videos.html)

***

#Lectures 

There are only **three lectures** for this module.

* A live introductory session (19 Jan, 11am)

* **Lecture 1** [Part A video](https://york.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=22db07bf-9bd5-4640-b40e-ac9200d2baf5) | [Part B video](https://york.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=479e77a5-0dc9-427b-8024-ac9200e9e965) | [PDF](http://www-users.york.ac.uk/~dj757/BIO00047I/lectures/BIO00047I-2020-Lecture1.pdf) | [Powerpoint](http://www-users.york.ac.uk/~dj757/BIO00047I/lectures/BIO00047I-2020-Lecture1.pptx) 

* **Lecture 2** [Video](https://york.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=843db01e-f33d-41e2-931c-aca800bef443) | [PDF](http://www-users.york.ac.uk/~dj757/BIO00047I/lectures/BIO00047I-2020-Lecture2.pdf) | [Powerpoint](http://www-users.york.ac.uk/~dj757/BIO00047I/lectures/BIO00047I-2020-Lecture2.pptx) 

* There are also **four short introductory videos** for each data set that you should watch:

* [Brassica intro](https://york.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=69f1df55-1182-4a4a-8bdc-ae1b00c3921a)

* [Yeast intro](https://york.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=3e9cbbfc-ef8c-4c2c-97b3-ae1b00c372bf)

* [Metagenomics intro](https://york.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=f51d7e94-63e5-480c-8d82-ae1b00c37872)

* [Macroevolution intro](https://york.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=dc0bd9f1-c1d0-4864-a298-ae1b00c37100)


There are other short videos to watch throughout the term. See the [week by week guide](https://vle.york.ac.uk/webapps/blackboard/execute/content/blankPage?cmd=view&content_id=_3999746_1&course_id=_99703_1) on the VLE for this.

***

#The assessement
The assessment for this module is a report describing an analysis of data (maximum 1500 words).
A description of what we want to see, and how we will mark the report is [here](https://www-users.york.ac.uk/~dj757/BIO00047I/misc/BIO00047I-report-guide-and-marking-scheme-2022.pdf)

**The assessment deadline is: Thursday 21nd of April 2022 at 11am**

***

#Workshops

There are five workshops for this module. You should attend though **all of them**. In workshops 1-4 you sould run throgh the exercise sfor your favouite two data sets. All the workshop material is [here](http://www-users.york.ac.uk/~dj757/BIO00047I/workshops.html). In [workshop 5](https://www-users.york.ac.uk/~dj757/BIO00047I/workshop5.html), we'll look at report writing. 

***
*Feel free to use and/or modify any R code from the workshops.*

***


#The Google Hangout
We use a Google Hangout to share questions/answers, plots and R code during the workshops. You can join [here](https://hangouts.google.com/group/HyPgPhKoJPKDY4uCA). 
Some people find the R code on the Hangout useful as a resource. *Use of the Hangout is optional.*<br>

As your posts to the Google Hangout are personal data, we comply with General Data Protection Regulation (GDPR). You can read about this, and some rules for good conduct [here](http://www-users.york.ac.uk/~dj757/BIO00047I/misc/BIO00047I-GoogleHangout.pdf).


***

#Getting help
Big data analysis isn't always easy. But **you** can do it. Here's how to get help if you are stuck:

1. **Problems with R code.** Read your code *very carefully*. Make sure you have closed all the brackets, not missed out a comma etc. That is often the problem.
2. Check out our video guides [here](http://www-users.york.ac.uk/~dj757/BIO00047I/videos.html).
3. Post your question on the [Google Hangout](https://hangouts.google.com/group/HyPgPhKoJPKDY4uCA).
4. Ask one me (Dan), Andrea, Katie, Daphne or of the tutors during a workshop. We are nice people :-)
5. Post your question on the VLE discussion board.


#Outro

**We hope you enjoy this module.** Even if it wasn't strictly *fun* the skills you learn here will help in 3rd year, and beyond. Your R Studio data analysis skill can be used in all kinds of jobs. So mention your proficiency in data analysis on your CV.

![](pics/array.png)
