An Introduction to Data Normalization in Bioinformatics Workflows
Intent and Scope This article introduces the concept of data normalization in bioinformatics workflows. It is intended for educational purposes only and does not provide medical, regulatory, or analytical guidance. 1. What Is Data Normalization? Data normalization is the process of adjusting values in a dataset to reduce technical variation while preserving meaningful biological signals. In bioinformatics, normalization is commonly applied to high-throughput data such as gene expression, sequencing counts, and other molecular measurements. Without normalization, comparisons across samples or experimental conditions can be misleading due to differences in data scale or measurement bias. 2. Why Normalization Is Essential in Bioinformatics Bioinformatics datasets often combine data generated under varying conditions, platforms, or protocols. These inconsistencies can introduce technical noise that obscures true biological patterns. Normalization helps: Improve comparability...