28-30 January 2020
Instructors: Toby Hodges, Florian Huber, Fotis Psomopoulos
Helpers: Malvika Sharan, Georg Zeller, Thea Van Rossum, Gaurav Diwan, Nicolai Karcher, Renato Alves
Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
On the first two days of this workshop we will cover basic skills in data organisation and analysis, using the statistical programming language R. On the third day we will introduce other advanced analysis methods in R using a transcriptomic dataset (although any researcher with an interest in multi-dimensional data will also benefit from the materials covered on this day).
For more information on what we teach and why, please see our paper "Good Enough Practices for Scientific Computing".
Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.
When: 28-30 January 2020. Add to your Google Calendar.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).
Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email email@example.com for more information.
Please be sure to complete these surveys before and after the workshop.
Digital data recording often starts with a spreadsheet software (e.g. Excel). For an effective data analysis, it's crucial to start with a well structured and formatted dataset. Because of this, before diving into R, we will start by having a discussion about common issues that should be considered when recording data in spreadsheets.
This lesson will cover the very basics of using R with RStudio.
This lesson will cover some functions to effectively manipulate and summarise
tabular data using the
This lesson teaches you how to use the
ggplot2 R package to make
a wide range of plot types.
In this session we will apply the concepts learned so far to a worked example of an exploratory data analysis of transcriptomic data.
During the lesson, we will also learn a few more tricks in R, including:
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
To participate in a Data Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.
We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.
Please visit the setup instructions for each lesson that will be covered in your workshop: