Resources - Gregory Lab

Here is a non-exaustive list of resources that our lab finds useful.

jenna.gregory@abdn.ac.uk

Statistics

Nature core collection: Stats for Biologists Full Collection of papers; Statistics in Biology and Practical Guides: https://www.nature.com/collections/qghhqm

Coding Nature Methods’ Points of Significance column on statistics explains many key statistical and experimental design concepts: https://www.nature.com/collections/qghhqm/pointsofsignificance

Coding general

Lists with links for online courses for machine learning and data science from MLTut.com

Online Courses

R

R Tutorials (from Coding Club; Uni of Edinburgh) including R Basics, Data manipulation, Data visualisation, Data synthesis, Modelling, Spatial data, Reproducible research: https://ourcodingclub.github.io/tutorials.html

R for Data Science: This website/book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it and visualize. https://r4ds.hadley.nz/

The R Graph Gallery: a collection of charts made with the R programming language:

https://r-graph-gallery.com

Systematic Reviews and Meta-Analyses

PRISMA

(Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is an evidence-based minimum set of items aimed at helping scientific authors to report a wide array of systematic reviews and meta-analyses.

Most recent PRISMA statement: PRISMA 2020, 27-item checklist, an expanded checklist that details reporting recommendations: https://www.bmj.com/content/372/bmj.n71

Guides

Cochrane Handbook for Systematic Reviews of Interventions

https://training.cochrane.org/handbook/current

How to conduct a meta-analysis in eight steps: a practical guide (paper)

https://link.springer.com/article/10.1007/s11301-021-00247-4

A brief introduction of meta-analyses in clinical practice and research:

https://onlinelibrary.wiley.com/doi/full/10.1002/jgm.3312

A 24-step guide on how to design, conduct, and successfully publish a systematic review and meta-analysis in medical research:

https://link.springer.com/article/10.1007/s10654-019-00576-5

Meta-evaluation of meta-analysis: ten appraisal questions for biologists

https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0357-7

RevMan (Systematic review and meta-analysis software)

About RevMan:

RevMan Web quickstart guide

https://training.cochrane.org/online-learning/core-software/revman

RevMan Knowledge Base

https://documentation.cochrane.org/revman-kb/

RevMan 5.4 (Desktop – soon to be discontinued) User Guide:

Click to access RevMan5.4_user_guide.pdf

RevMan (Desktop – soon to be discontinued) Short Tutorial Series (a playlist of 43 short videos)

metafor (R software for conducting meta-analyses)

Resources for getting started with the metafor package written by Wolfgang Viechtbauer:

Viechtbauer, W. (2010). Conducting Meta-Analyses in R with the metafor Package. Journal of Statistical Software, 36(3), 1–48. https://www.jstatsoft.org/article/view/v036i03

Metafor website: https://www.metafor-project.org/doku.php/metafor

Meta-Analysis with R Workshop: https://github.com/wviechtb/workshop_2022_ma_esmarconf

R Code for Meta-Analysis Books: https://github.com/wviechtb/meta_analysis_books