Previous versions were lauded as "magnificent" and "ideal" for introducing varied statistical methods. The 2019 edition is considered a necessary acquisition even for those owning earlier versions due to the rapid evolution of genomic data analysis.
How do we link genes to disease? This part covers the mechanics of Genome-Wide Association Studies (GWAS), including quality control (QC), correction for multiple testing (Bonferroni vs. FDR), and meta-analysis. A new chapter in the 2019 edition focuses on , acknowledging that common variants only explain a fraction of heritability. Balding D. Handbook of Statistical Genomics 2019
Features dedicated sections on statistical aspects of data from modern sequencing, including sequence-based functional assays. Previous versions were lauded as "magnificent" and "ideal"
This is the "NGS" section. It explains the statistical underpinnings of RNA-Seq (expression analysis), ChIP-Seq (protein-DNA binding), and metagenomics. The chapter on is particularly vital, teaching how to remove technical artifacts (batch effects) that can swamp biological signals. This part covers the mechanics of Genome-Wide Association
For evolutionary biologists, this section provides rigorous coverage of substitution models (JC69, GTR) and tree-building methods (Maximum Likelihood vs. Bayesian MCMC). The chapter on "Molecular Clocks" has been updated to reflect the Bayesian approaches popularized by software like BEAST.