Genomics

General course

• Introduction to Genomics for Engineers

Machine Learning

Feature selection

• How to Choose a Feature Selection Method For Machine Learning

AI

Learning resources

• Video
  • 50 Days of Deep Learning by Mısra Turp
• Books
  • Understanding Deep Learning by Simon J.D. Prince

AI & Genomics

Tips for modeling

• Markowetz, F. All models are wrong and yours are useless: making clinical prediction models impactful for patients. npj Precis. Onc. 8, 54 (2024). https://doi.org/10.1038/s41698-024-00553-6

Deep learning application in genomics

• Zou, James, et al. “A primer on deep learning in genomics.” Nature genetics 51.1 (2019): 12-18.
• Caudai, Claudia, et al. “AI applications in functional genomics.” Computational and Structural Biotechnology Journal 19 (2021): 5762-5790.

Books for reading

• Book: Deep Learning in Bioinformatics
• Book: Deep Learning for Genomics: Data-driven approaches for genomics applications in life sciences and biotechnology

Bioinformatics

General tips

• Project management
  • A Quick Guide to Organizing Computational Biology Projects
  • Ten Simple Rules for Reproducible Computational Research
• Development
  • Ten simple rules for biologists learning to program
  • Good enough practices in scientific computing
  • Best Practices for Scientific Computing

Functional analysis

• Gene Ontology
  • EBI: Gene Ontology and GO Annotations
• Packages
  • Biomedical Knowledge Mining using GOSemSim and clusterProfiler

Single-cell data analyses

• General learning materials
  • Getting Started with Seurat
  • Analysis of single cell RNA-seq data
  • Single-cell RNA-seq workshop
  • Workshop: Single-Cell RNA-Seq Analysis by UCLA QCBio Collaboratory
• Seurat examples
  • Seurat Example Workflow (www.bioinformatics.babraham.ac.uk)
  • Seurat - Guided Clustering Tutorial
• Quality control
  • hbctraining: Single-cell RNA-seq: Quality control
• Automatic cell type annotation
  • Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data

Methylation analysis

• Data processing for Bisulfite-Sequencing
  • nf-core/methylseq: Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark or bwa-meth + MethylDackel
• Analyses tools for Bisulfite-Sequencing
  • Tutorial of methylKit
  • Tutorial of dmrseq
  • Tutorial of BSseq
  • Tutorial of DSS
• Analysis for Illumina’s methylation arrays
  • Tutorial of minfi

Visualization

• Making a heatmap in R with the pheatmap package

Sequencing technologies

Single-cell sequencing

• ParseBioscience: Evercode™ Whole Transcriptome

Methylation sequencing

• NEBNEXT® Enzymatic Methyl-seq Workflow

Programming

GitHub

• GitHub Actions
  • Workflow syntax for GitHub Actions
• Gitbook
  • Simple tutorial on hosting your Gitbook documentation on Github pages (bonus: with Gitbook Editor)

Shell scripting

• Tutorials in general
  • Introduction to the Command Line for Genomics
• Specific programs
  • Guide to Using Umask Command in Linux
  • How To Use Linux Screen

R

• renv
  • Introduction to renv
  • Things that can go wrong when using renv
• Tidyverse packages
  • dplyr
    • Dplyr Essentials (easy data manipulation in R): select, mutate, filter, group_by, summarise, & more
    • Dplyr Advanced Guide: data cleaning, reshaping, and merging with lubridate, stringr, tidyr, ggplot2
    • dplyr cheatsheets
  • tidyr
    • tidyr cheatsheets -visualization
  • Curated resources for Data Visualization, Drawing & Publishing in R by krzjoa

Mojo

• Introduction
  • Jeremy Howard demo for Mojo launch (Video)
• Documentation
  • Mojo🔥 Doc

IDE

• AI-assistance
  • Generative AI in Jupyter
  • Jupyter AI

Scientific skills

Writing

• Articles
  • Cooper, I. Diane. “How to write an original research paper (and get it published).” Journal of the Medical Library Association: JMLA 103.2 (2015): 67.

Visualization

• RAWGraphs: A free and open source tool for data visualization

Proteomics

• General introduction
  • Introduction to Proteomics 2021 EMSL Summer School
  • Mass Spectrometry-Based Proteomics 2021 EMSL Summer School
• Proteomics analysis
  • nf-core/quantms: Quantitative mass spectrometry workflow
  • nf-core/proteomicslfq: Proteomics label-free quantification (LFQ) analysis pipeline
  • nf-core/diaproteomics: Automated quantitative analysis of DIA proteomics mass spectrometry measurements
  • Proteomics Data Analysis in R/Bioconductor