"This book is a good tool for self-learning analytical strategies for omics data. It requires previous knowledge of R and focuses on getting things done...I think the book would be a good reference for masters or PhD students that have to perform their analysis and need a starting point. Also, for the practicing statistician working with omics data."- Victor Moreno, ISCB News, July 2020"Omic Association Studies with R and Bioconductor is an excellent tool book for those looking to have hands-on guidance to analyze multiomics datasets using established packages. The authors provide comprehensive examples of using genomic, transcriptomic, epigenomic, and exposomic data, as well as their integration, to generate biological hypotheses and explore individual heterogeneity."– Biometrics