The COVID-19 Resource Centre, established by Elsevier in January 2020, provides free information in English and Mandarin on the novel coronavirus. Elsevier grants permission to make all COVID-19-related research available in PubMed Central and other public repositories, allowing unrestricted reuse and analysis with acknowledgment of the original source. The centre includes research content that can be accessed through the company's public news and information website, Elsevier Connect. The article also discusses statistical methods for detecting molecular adaptation, focusing on the nonsynonymous/synonymous ($d_n/d_s$) rate ratio. It explains how this ratio measures the difference between synonymous and nonsynonymous substitution rates, with an $\omega$ ratio significantly higher than one indicating diversifying selection. The article reviews various estimation methods for $d_n$ and $d_s$, including approximate methods and maximum likelihood (ML) methods, and their strengths and weaknesses. It highlights the importance of considering transition/transversion rate biases and codon usage biases in estimation procedures. Additionally, the article explores methods for detecting lineage-specific episodes of Darwinian selection and amino acid sites under positive selection. It discusses the limitations of current methods and suggests future directions for improving their power and accuracy. The article emphasizes the need for more realistic evolutionary models that account for various factors such as recombination, sequence divergence, and the size of the gene.The COVID-19 Resource Centre, established by Elsevier in January 2020, provides free information in English and Mandarin on the novel coronavirus. Elsevier grants permission to make all COVID-19-related research available in PubMed Central and other public repositories, allowing unrestricted reuse and analysis with acknowledgment of the original source. The centre includes research content that can be accessed through the company's public news and information website, Elsevier Connect. The article also discusses statistical methods for detecting molecular adaptation, focusing on the nonsynonymous/synonymous ($d_n/d_s$) rate ratio. It explains how this ratio measures the difference between synonymous and nonsynonymous substitution rates, with an $\omega$ ratio significantly higher than one indicating diversifying selection. The article reviews various estimation methods for $d_n$ and $d_s$, including approximate methods and maximum likelihood (ML) methods, and their strengths and weaknesses. It highlights the importance of considering transition/transversion rate biases and codon usage biases in estimation procedures. Additionally, the article explores methods for detecting lineage-specific episodes of Darwinian selection and amino acid sites under positive selection. It discusses the limitations of current methods and suggests future directions for improving their power and accuracy. The article emphasizes the need for more realistic evolutionary models that account for various factors such as recombination, sequence divergence, and the size of the gene.