Differential gene expression analysis is a critical step in many biological studies, from identifying potential biomarkers to understanding the molecular mechanisms underlying disease. R, a popular programming language among biologists, offers powerful tools for analyzing gene expression data. However, analyzing such data can be a challenging task, especially for beginners. In this blog post, we
Bioconductor is a widely used open-source software project that provides tools for the analysis and comprehension of high-throughput genomic data. It includes a vast collection of packages for the analysis of microarray and sequencing data, gene expression analysis, functional annotation, and visualization. In this blog post, we will provide a step-by-step guide for biologists to
