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How to Start Learning Bioinformatics and Not Get Intimidated (With R)
A Step-by-step Example using Differential Gene Expression Analysis
Introduction
This article is aimed towards people who are looking to “break into” the bioinformatics realm and have experience with R (ideally using the tidyverse). Bioinformatics can be a scary-sounding concept (as least it is for me) because it is such a vast and fast-developing field that it can be difficult to define exactly what it is. I’ve always thought that bioinformatics was a highly advanced field beyond what I was capable of doing — that I would need years of technical training to begin actually doing it. But like with everything, it doesn’t actually take much to begin doing something (it goes without saying that it does take years to master something).
Acknowledging that I’m oversimplifying, bioinformatics is essentially the in silico (or data-based) approach to answering biological questions. With the advent of more advanced sequencing technology and accompanying developments in statistical algorithms, we now have unprecedented access to biological data at a scale and price previously unheard of as well as the tools to extract insights from this data.
In this article, I aim to provide an example of an easy way that anyone who likes data, likes to work with R, and has an interest in this field, can start doing analyses in the bioinformatics realm.