Chapter 7 Key Resources
7.1 University-wide administration
- Annual leave
- Diversity travel (UoE travel booking system - requires registration; before booking, discuss with Emily/Malcolm about which grant you should claim from
- People and Money (UoE expenses, payments, etc.) - requires sign in
7.2 Centre for Clinical Brain Sciences
- CAMARADES sits within the Centre for Clinical Brain Sciences. Navigate to the CCBS staff web pages for more information on policies and people to contact.
7.3 Common CAMARADES resources and acronyms
- ASySD: Automated deduplicator tool for removing duplicates across systematic searches, developed in-house.
- Juniper: A supercomputer utilized for complex data analysis and research simulations. We use it daily for coding in R via RStudio Server. If you want to use this, ask Kaitlyn to create a new user for you, and use your login details to access the R Studio Server via this link
- SOLES: Systematic Online Living Evidence Summaries, a pipeline and dashboard summarising the latest research findings in a given research area.
- Sprints: SyRF and SOLES development teams use time-boxed periods (usually two weeks) called “spints” to work on specific features or goals. We refer to meetings about the sprint as “sprint planning”, “sprint retrospective” and “sprint catchup”.
- SyRF: Our in-house systematic review platform. We use it for screening for inclusion and extracting information and data from publications. Head to the SyRF website
- GALENOS: Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis https://www.galenos.org.uk/
- iRISE: Interventions to Improve Reproducibility in Science
- GitHub: Central platform for code sharing and collaboration on various projects.
- SharePoint: We use sharepoint to manage our files and folders. This is accessible via Teams by going to the “Files” tab.
- Teams: We use Microsoft Teams for day-to-day communication and file-management. You will get an invite to join on your first day.
- Zulip: An open-source messaging app for better team communication and collaboration. We often use this to communicate with those outside of our immediate Edinburgh Team. Sign up here.
- Zenhub:
7.4 Training / reading list
Here is an growing list of resources you might find useful.
7.4.1 Translational failure
Course: Edinburgh University Research Optimisation Course: course on improving preclinical research
- Log in to Learn
- Click on ‘self-enrol’ (top right of the screen)
- Scroll down to Research Improvement
- Click on EUROC (Edinburgh University Research Optimisation Course)
7.4.2 Why systematic reviews?
Publication: Sena ES, Currie GL, McCann SK, Macleod MR, Howells DW. Systematic reviews and meta-analysis of preclinical studies: why perform them and how to appraise them critically. J Cereb Blood Flow Metab. 2014 May;34(5):737-42.
7.4.3 Systematic review methodology
CAMARADES Berlin Wiki page for preclinical systematic reviews
Systematic review introductory videos by CAMARADES Edinburgh
CAMRADES Berlin Introductory Workshop on preclinical systematic reviedws
7.4.4 Data skills
Online self study materials with different pathways for varying levels of prior knowledge (Excel, R, Python, SQL).
7.4.5 R
R is a programming language we use day-to-day in CAMARADES to develop evidence synthesis pipelines, automate steps of the review process, and to perform analyses.
Download Swirl- an interactive intro course that also goes through the steps of installing R and RStudio.
Improve your workflow for reproducible science weblecture (1hr, 51m) - an intro to using R reproducibly by using tools like RMarkdown, Git and GitHub
Online book - using R for Data Science
RStudio cheatsheets
Tidyverse: collection of R packages for data science
Online book - use R Markdown to weave narrative text and code and produce parameterised/reproducible documents (html/pdf/word).
R Shiny : create interactive web applications using R
Git/Github -learn about version control using Git and Github
7.4.6 Meta analysis
Methods paper on meta analysis including statistical tests and formulas required:
Online book - Doing Meta Analysis in R by Mathias Harrer
Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2021). Introduction to meta-analysis. John Wiley & Sons. (Electronic and hard copies available from UoE library)
7.4.7 Data Visualisation
Data visualisation inspiration using R - a gallery of R visualisations
Helpful guide on which visualisations to use and how to create them