What is this workshop about?

Data Carpentry workshops are for any researcher who has data they want to analyse, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills, and tools for working more effectively with data. We will cover data organisation in spreadsheets, data cleaning, SQL, the command line, and R for data analysis and visualisation using examples from biology. Participants should bring their laptops and plan to actively participate. By the end of the workshop, learners should be able to more effectively manage and analyse data and apply the tools and approaches directly to their ongoing research.

Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.

Target Audience:

The course is aimed at researchers in the life science and computational science disciplines at all career stages. We particularly encourage students and post-doctoral scientists to attend, but the course is open to everyone.

Prerequisites:

There are no pre-requisites, and we will assume no prior knowledge about the tools.

What is the workshop about?

A substantial part of the course will be devoted to bioinformatics resources and tools relevant in metagenomics data analysis. Participants will start at the bench and end in front of the computers for a problem solving activity utilizing the bioinformatics training they will be receiving during the course.

What will it cover?

To provide an overview of the main aspects involved in metagenomics from the bench to data analysis and discussion around the interpretation and actual examples of the impact and applications of metagenomics derived research.

What will I learn?

• An overview of NGS for metagenomics and metatranscriptomics including current projects
• Knowledge of 16S Experimental Design including primer design and sources of error
• Hands on experience in: DNA isolation, QC of the DNA, NGS library construction and loading the sequencing platform
• An overview of software for analysis and interpretation of metagenomics datasets and some basic analytical workflows
• Hands-on experience of a case study dataset including FastQC, trimming and host removal
• Understanding assembly principles and the latest metagenomics assembly tools
• Hands on experience in metagenomics assembly
• Using MEGAN to explore metagenomic and metatranscriptomic data including taxonomic and functional annotation, multiple comparison methods and production of publication quality images
• An overview and hands on experience in public data resources for metagenomics e.g. IMG/M, EBI Metagenomics, MG-RAST

Target Audience:

This course is aimed at advanced PhD students and post-doctoral researchers who are doing or planning to start research in the field of metagenomics.

Scientific Organisers:

• Emily Angiolini, Earlham Institute (EI), UK
• Kirsten McLay, Earlham Institute (EI), UK
• Leah Catchpole, Earlham Institute (EI), UK
• Richard Leggett, Earlham Institute (EI), UK
• Mark Alston, Earlham Institute (EI), UK

What is the workshop about?

The course will provide an overview of bioinformatics from sequence searching, expression data, through to protein-protein interactions. You will receive an overview of common databases, tools and tasks, learn why, when and how to use the command line, and will finish with a session in groups focussed on answering a biological question using the tools learned over the course. The course comprises conceptual lectures, hands on exercises, and group activities. It also provides ample opportunities to interact with expert trainers, motivated researchers and your fellow trainees.
 

What will I learn?

• Basic understanding of when it is important to use the command line, plus learning some basic skills
• Overview of databases for raw DNA sequences, reference sequences and protein sequences
• Sequence retrieval tools, genome databases and gene prediction
• Multiple sequence alignments tools
• Understand what an ontology is, and how it is used
• Be familiar with the Gene Ontology and the analyses it supports
• Know how to search and use the Gene Ontology in your project
• Overview of protein-protein interaction (PPI) networks, experimental methods to detect PPIs, tools and applications to visualise and analyse PPIs.
• Insight into the basic biological mechanisms of transcription-factor (TF) mediated gene expression, databases containing experimentally verified TF- target information and various tools and resources available to reconstruct de novo the transcriptional regulatory networks of non-model organisms.
• Browse the UniProt database in detail, learning about its structure and the type of data it contains
• Understand how to browse, query and retrieve data from the Expression Atlas
• Understand the data flow from ArrayExpress database and how we control the quality of data sets in the Atlas

Target Audience:

This course is aimed primarily at PhD students and early career postdocs. You will ideally have a project in the near immediate future or still in the early stages of development related to the subject matter of this course. You will be new to the area of bioinformatics and want to get a feel for the range of tools available for analysis of your data. The selection committee will be looking at the overlap between the applicants’ expectations from the course and what the course will be delivering, coupled with the timely application of skills learned during the course to their research.

Important information
Please note, you will be required to bring your own laptop for the purposes of this workshop.

What is this workshop about?
Our goal is to help scientists become more productive by teaching them basic computing skills like program design, version control, testing and task automation. In this two-day bootcamp, short tutorials will alternate with hands-on practical exercises. Participants will be encouraged both to help one another, and to apply what they have learned to their own research problems during and between sessions.

What are the objectives of the course?
You will learn to:

• use the shell to do more in less time
• automate your tasks and pipelines
• write structured programs
• use Git to manage and share information
• how (and how much) to test programs

Target Audience
The course is aimed at researchers in the life science and computational science disciplines at all career stages. We particularly encourage students and post-doctoral scientists to attend, but the course is open to everyone.

Prerequisites
This is aimed at trainees with very little or no prior knowledge of programming.