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


Nature core collection: Stats for Biologists Full Collection of papers; Statistics in Biology and Practical Guides:

Coding Nature Methods’ Points of Significance column on statistics explains many key statistical and experimental design concepts:

Coding general

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


R Tutorials (from Coding Club; Uni of Edinburgh) including R Basics, Data manipulation, Data visualisation, Data synthesis, Modelling, Spatial data, Reproducible research:

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.

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

Systematic Reviews and Meta-Analyses


(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:


Cochrane Handbook for Systematic Reviews of Interventions

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

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

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

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

RevMan (Systematic review and meta-analysis software)

About RevMan:

RevMan Web quickstart guide

RevMan Knowledge Base

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

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.

Metafor website:

Meta-Analysis with R Workshop:

R Code for Meta-Analysis Books:

Digital Pathology

QuPath: Open source software for digital pathology image analysis (Pete Bankhead)

The original QuPath paper:

QuPath tutorials:

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