A bioinformatician processes RNA-seq data from 45,000 genes. After quality control, 15% of genes are removed due to low expression. Of the remaining, 28% show differential expression under experimental conditions. How many genes are differentially expressed?

Sat, 02 May 2026 19:56:42 +0000

**How A Bioinformatician Processes RNA-Seq Data and What It Really Reveals** Every day, researchers and clinicians rely on powerful computational workflows to decode the complex language of genes—especially when analyzing RNA-seq data from hundreds of thousands of transcripts. At the core of this effort is a meticulous pipeline that begins with processing vast datasets containing data from tens of thousands of genes. When analyzing 45,000 initial RNA sequences, quality control plays a critical role, filtering out low-expression genes that add noise rather than insight. This step removes about 15% of input genes, ensuring only robust signals proceed to downstream analysis. From the remaining dataset, a key analysis reveals how gene expression shifts under experimental conditions. Of the genes that pass quality filters, 28% demonstrate differential expression—meaning their activity levels rise or fall significantly in response to treatment, disease, or environmental triggers. Translating these percentages into actual numbers shows that roughly 12,360 genes (28% of 44,100) are actively tuned in or out under specific conditions. With mobile and desktop readers seeking clarity on genomics’ real-world impact, this statistical snapshot reflects a fundamental rhythm of cellular response—one increasingly central to personalized medicine, drug discovery, and trait prediction research across the US.