Statistical Analysis of Gene Expression Data Using Bayesian Inference Methods in Biotechnology Research
Abstract
Bayesian inference offers a principled way to quantify uncertainty in gene expression studies, especially when biotechnology experiments have few biological replicates and noisy measurements. In practice, RNA-seq data often contain uneven library sizes, donor effects, low-count genes, outlier samples, and uncertain dispersion estimates. These problems are not minor technical details because they directly affect differential-expression calls. A realistic Bayesian analysis must therefore report bo
Fields of Study & Subjects
Gene expression and cancer classification
Molecular Biology Techniques and Applications
Statistical Methods in Clinical Trials
Publication details
- Journal / source
- Journal Of Biochemical Technology
- Publisher
- Polaris
- Volume
- 17
- Issue
- 1
- Pages
- 147–156
- Publication date
- 1 January 2026