This is a graduate-level course covering the fundamentals of transparent and reproducible bioinformatics, targeted towards biomedical students.
Lab01.ipynb: Introduces basic Unix commands commonly used in bioinformatics workflows. Covers commands like ls, cd, and file manipulation in a Unix environment.
Lab02.ipynb: Focuses on Unix scripting to automate tasks in bioinformatics. Demonstrates how to create simple scripts using bash for handling repetitive tasks.
Lab03.ipynb: Introduces Python programming for bioinformatics applications. Covers basic syntax, data types, and control structures relevant to biological data analysis.
Lab04.ipynb: Provides a setup guide and initial steps for using bioinformatics tools. Guides users through configuring their environment for data analysis.
Lab05.ipynb: Continues with setting up the computational environment for bioinformatics workflows. Covers additional configuration steps and essential bioinformatics software.
Lab06.ipynb: Further explores bioinformatics tools and environment setup for analysis. Introduces key tools and libraries used in data handling and analysis.
Lab07.ipynb: Introduces Git and GitHub for version control in bioinformatics projects. Guides users through repository creation, committing changes, and collaborating on code.
Lab08.ipynb: Explores the use of R in bioinformatics through Google Colaboratory. Introduces basic R syntax and data manipulation techniques in a cloud environment.
Lab09.ipynb: Introduces the use of Salmon for transcript quantification in RNA-seq data. Demonstrates how to align reads and interpret output files for gene expression analysis.
Lab10.ipynb: Guides users through working with a reference genome and sequence data. Demonstrates file manipulation using commands like head and visualization of genomic data.
Lab11.ipynb: Covers the setup of Miniconda and Mamba for managing bioinformatics environments. Introduces the use of Mamba for faster package management and environment handling.