PROGRAMMING

Programming is a fundamental skill in bioinformatics, enabling you to make sense of complex datasets. After preprocessing your sequencing data in a bash environment, you’ll often end up with files like count matrices that need further analysis and visualization. This is where programming becomes your most valuable tool, helping you transform raw data into meaningful insights.

For basic analysis and visualization, you can use almost any programming language. However, R and Python dominate the bioinformatics landscape, as many widely used packages are written in these languages. As a result, most bioinformaticians work with R, Python, or often both.

Beyond data analysis, bioinformatics can also involve developing software tools or packages for others in the field. For these tasks, adopting an Object-Oriented Programming (OOP) approach can be more effective than writing basic scripts. Python and Java are popular choices for such projects. However, this guide will focus on helping you get started with scripting in R and Python, leaving the complexities of OOP for another day.

If you’re new to programming, starting with Python is a great idea. Its straightforward syntax and versatility make it beginner-friendly. Once you’re comfortable with Python, picking up R will feel much easier. For now, focus on one language to build your confidence and avoid feeling overwhelmed.