Bioinformatics Tools

A hands-on course for MSc biology students

Author

Affiliation

Corentin Maslard, PhD

UniNE

Abstract

Student website for the Bioinformatics Tools course: nine sessions introducing the essential command-line, R, and machine-learning tools used to inspect, analyse, and interpret biological data.

Preface

Contributors: Corentin Maslard, postdoctoral researcher in Joop E.M Vermeer lab team

This website is the course support for Bioinformatics Tools, a practical course for MSc biology students at the University of Neuchâtel.

The course uses examples from genomics, microbial ecology, and plant biology, and introduces machine learning or deep learning as a tool for answering biological questions.

TipPlease feel free to contact me for:

• Internship
• Information
• Help with your future analyses

NoteMore informations about my work :

• Personal website
• Email
• Github
• Linkedin

• ORCID
• ResearchGate
• Google Scholar

• X (Twitter)
• HAL
• CV

Getting started

This site collects the written supports for the nine sessions of the course. Each session has its own practical.qmd chapter with the exact steps to follow during the practical.

• Format: nine sessions, 14:15-17:00 - about 45 min of theory, 1 h 50 of practice, 10 min break.
• Level: deliberately simple and progressive; no prior programming experience is assumed.
• Language: all written supports are in English.
• Data: small teaching datasets are prepared in advance; no long installation or large download during class.

Course programme

1. Initial diagnostic and essential commands
2. Shell, biological formats, and quality control
3. Sequence similarity and phylogeny
4. Biological tables and visualisation with R
5. PCA and unsupervised learning
6. Genome-wide association (GWAS) in Arabidopsis
7. Introduction to deep learning
8. Guided project: question, script, and first result
9. Guided project: correction, interpretation, and presentation

ImportantAssessment

Sessions 1 and 2 are practice: they are not graded. The continuous assessment starts at Session 3: a short individual Moodle quiz (about 15 minutes) at the end of each session, based on the results actually obtained during the practical. The guided project (Sessions 8 and 9) is assessed separately.

Licence

This document is made available under the terms of the Licence Creative Commons Attribution - Non Commercial Use - Share Alike 4.0 International.

Package used in this quarto document

library(renv) # install.packages("renv")
library(dplyr)

deps <- renv::dependencies(path = ".", progress = F, quiet = T)

unique_packages <- unique(deps$Package)
writeLines(unique_packages, here::here("src/packages_use_in_this_quarto.txt"))

data.frame(
  Package = unique_packages,
  Version = sapply(unique_packages, function(pkg) {
    tryCatch(as.character(packageVersion(pkg)), error = function(e) NA)
  }),
  stringsAsFactors = FALSE
) %>%
  #knitr::kable(caption = "List of packages used in this document", row.names = FALSE)
  DT::datatable(.,
  filter = "top",
  class = 'cell-border stripe',
  rownames = FALSE
)