Analytics 1: Introduction to reproducible analyses in R: 15-20 May 2020

When

This course was originally due to run from 10am to 4pm Thursday 19th March 2020.

Due to COVID-19 lock down, the course has been moved on-line and will take place on the following dates from 15th to 20th May 2020:

May 15: Release set up instructions 

Expected audience: Those without previous experience

May 18, 1400-1530 Office hours to assist with set up  

Expected audience: Those without previous experience

May 19 1100 – 1130 Introduction and Principles of reproducibility

Expected audience: Everyone

May 20 1000-1200 Introduction to R and working with data.

Expected audience: Those without previous experience

May 21 1300-1330 RStudio Projects.

Expected audience: Everyone

May 21 1400-1530 Tidying data and the tidyverse including the pipe.

Expected audience: For those with previous experience (workshops aimed at those without previous experience may be sufficient).

May 26 1000-1130 Advanced data import.

Expected audience: For those with previous experience (workshops aimed at those without previous experience may be sufficient).

May 28 1300-1500 R Markdown for Reproducible Reports.

Expected audience: Everyone

Where

Dept of Biology, The University of York, Wentworth Way, YORK. YP10 5DD

How to find the Dept of Biology at York – Main Atrium

Who it is for

This course is mandatory for White Rose BBSRC DTP and CASE students who are in Year 1 (2019 starters).

NOTE: This is a two part, mandatory training session for DTP students.  Analytics 1: Introduction to reproducible analyses in R will be held for first years (2019 starters) in Spring 2020 on-line.  This will be followed by Analytics 2 for the same cohort (who will then be in Year 2) in Spring 2021 in Sheffield.

Course content

An increase in the complexity and scale of biological data means biologists are increasingly required to develop the data skills needed to design reproducible workflows for the simulation, collection, organisation, processing, analysis and presentation of data. Developing such data skills requires at least some coding, also known as scripting. This makes your work (everything you do with your raw data) explicitly described, totally transparent and completely reproducible. However, learning to code can be a daunting prospect for many biologists! That’s where an Introduction to reproducible analyses in R comes in!

R is a free and open source language especially well-suited to data analysis and visualisation and has a relatively inclusive and newbie-friendly community. R caters to users who do not see themselves as programmers, but then allows them to slide gradually into programming.

Prerequisites

No previous coding experience will be assumed.  Those with previous R coding experience will have additional and more advanced exercises to work on.

Learning outcomes

After this workshop the successful learner will be able to:

  • Find their way around the RStudio windows
  • Create and plot data using the base package and ggplot
  • Explain the rationale for scripting analysis
  • Use the help pages
  • Know how to make additional packages available in an R session
  • Reproducibly import data in a variety of formats
  • Understand what is meant by the working directory, absolute and relative paths and be able to apply these concepts to data import
  • Summarise data in a single group or in multiple groups
  • Recognise tidy data format and carry out some typical data tidying tasks
  • Develop highly organised analyses including well-commented scripts that can be understood by future you and others
  • Use R Markdown to produce reproducible analyses, figures and reports

Tutor

The course will be delivered by Emma Rand of The University of York.

Refreshments

Not applicable for the on-line course.

Travel arrangements

Not applicable for the on-line course.

How to register

Registration was done earlier in the year, prior to the original March date.  You do not need to register again.  However, please note the following:

A reminder: This course is mandatory for current first years (2019 starters).  If you were unable to attend the original date in March, please confirm with the tutor, Emma Rand (emma.rand@york.ac.uk) that you can now attend the on-line course during May 2020.  

Contact

For any queries about the course, please contact the tutor, Emma Rand: emma.rand@york.ac.uk

For general DTP queries, contact Catherine Liddle

White Rose BBSRC Doctoral Training Partnership Co-ordinator

Student Education Service | Doctoral College
Faculty of Biological Sciences

7.82 Irene Manton Building | University of Leeds | Leeds LS2 9JT
Tel +44 (0)113 343 6463 | Ext 36463
E-Mail: c.m.liddle@leeds.ac.uk

DTP website: https://www.whiterose-mechanisticbiology-dtp.ac.uk/