Links and other useful tutorials

(Updated: April, 13th, 2023)

Here is a list of some useful tutorials and other materials compiled by Deisy Morselli Gysi, a bioinformatician I admire. There are also materials of courses I took, mainly about whole-exome sequencing data analysis.

DataViz 📊

Presenting your results in a visual appealing manner is as important as your analysis. Follows a couple of sources of how to make different visualizations - and mainly - when to use them 😄.

• From Data to Viz.
  • Shows the most correct way to DataViz
  • Has examples in R and d3. <3
• Vega and d3
• Color Scale for diff viz type
• Data Vis with R - Book

Data Science, Statistics and Machine Learning 💻

Analyse your data, perform the right hypothesis testing, use the right model, learn how to do inference in the right way:

• Cool book on DS

  • Not deep, and much more on the application side, instead on the theory.

• Stats for Biologists

  • Quite useful for basic stats

• Basic DS

  • Basic tools for DS.

• Basic Stats and data analysis for biologists

• Statistical Inference via Data Science

  • A pretty cool and decent book on Inference and DS

• The amazing book from Susan Holmes

• A guide to ML - in Portuguese

• A guide to Machine Learning & Bioinformatics

• Survival Analysis - I

• Survival Analysis - II

• Survival - Thomase Love’s tutorial

• TSA - Time Series Analysis

• GLM - Generalized Linear Models

  • A very very gentle intro to GLMs

• GLM - Generalized Linear Models - In Portuguese

  • From Prof. Gilberto de Paula.

• GLM: The paper from Nelder

• GLMM: Statistical inference in generalized linear mixed models: a review

• How to use GLMM in biology (paper) - Generalized linear mixed models: a practical guide for ecology and evolution

• GAMs

  • The best tutorial on GAMs <3

• GAMLSS

  • The package webpage. With tons of examples.

• Intro to Deep Learning - Video

• Deep Learning - Book

• ML with graphs

• ML with graphs II

• Graph Representation Learning

• GNN

• Tutorials for G(C)NNs

• TensorFlow tutorial

Network Science 🕸️

Learn Network Science.

• Awesome Network

  • Massive repo on many tools for NetSci.

• Network Science Book

  • Albert-Laszlo Barabasi Book on Network Science.

• Network Analysis with R

• Guide to NetVis

• Interactive vis visNetwork

  • Interactive Networks (useful for shiny)

• How to use igraph

• How to use igraph - II

Network Medicine 🧪

• Network Medicine Tutorial
• Network Medicine and Gene-Co-expression Networks

Bioinformatics 🧬

Bioinformatics basic tools.

• Awesome Bioinf - A guide to almost everything in Bioinf

Whole-Exome Data Analysis 🧬

• Lucia Spangenberg’s WES tutorial
• Hugo Naya’s WES/pop. genomics tutorial

NGS 🧬

• A Gentle Intro to NGS
• Another intro for NGS
• And… another
• RNAseq Workflow
• Diff Expression
  • A Tutorial for PEB2020
• Michael Love Tutorials
  • Yes, his tutorials are always great.

Phylogeny 🐣

• How to create trees
• MUSCLE webpage
  • Tool for creating the aligment & trees
• Tutorial from EVOLUTION AND GENOMICS
• Plot Trees

R 💻

Some brief tutorials to learn R.

Tidy* 📦

• Learn Tidyverse
• Model with Tidy
  • All tools for DS
• R4DS

Markdown ✍️

• Is it your first time using markdown? Check this short tutorial
• Improve the Rmd skills
• Bookdown
• Making your md pretty using Distill

Shiny 🖱️

Make your results interactive. And shine ✨

• Mastering Shiny