Omic Association Studies with R and Bioconductor

“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

Juan R. González is an Associate Research Professor leading the Bioinformatics Research Group in Epidemiology at Barcelona Institute for Global Health. He has published extensively on methods and bioinformatics tools to detect structural variants from genomic data and to perform different types of omic association studies. Dr. González is the author of a large number of R and Bioconductor packages including state-of-the-art libraries such as SNPassoc or MAD that have been used to discover new susceptibility genetic factor for complex diseases.

Alejandro Caceres is a Senior Statistician in the Bioinformatics Research Group in Epidemiology at Barcelona Institute for Global Health. He has large experience in developing new statistical methods to exploit genomic, transcriptomic and epigenomic data obtained from public repositories. Dr. Cáceres is the author of several R and Bioconductor packages that have been used, for instance, to study the role of polymorphic genomic inversions in complex diseases or to investigate how the downregulation of chromosome Y may affect age-related diseases.