Precision Health with Multi-Omics and Environmental Data: A Primer
Preface
Integrating environmental data with biological data from multiple omics datasets can help provide unprecedented insights into the complex interplay of environment and biology. Joint analysis of environment and multi-omics can provide a more comprehensive picture of individual health and disease than individually analyzing datasets. However, to harness the full potential of using multi-omics data to understand environmental and biological drivers of disease, researchers need a robust framework for understanding how and why to perform different multiomic integration techniques.
This book is intended as a resource for researchers aiming to incorporate omics datasets to understand how environmental or biological factors impact human health and disease. We aim to explain the concepts, techniques, and methodologies that allow researchers to fully leverage the information in multidimensional datasets to obtain biologically relevant and actionable insights into environmental and biological impacts on disease.
This book has three sections corresponding to each column shown in Figure 1. In Chapter 2, we provide an example of high dimensional mediation with early, intermediate, and late integration, as shown in the first column of Figure 1. In Chapter 3, we provide an example of mediation with latent factors, a two-step approach that first uses dimensionality reduction on the omics datasets and then performs mediation on the resulting factors, as shown in the second column of Figure 1. In Chapter 4, we provide an example of quasi/intermediate integration, an approach where information on environmental factors and information on multiple omic layers are analyzed jointly in a single unified analysis, as shown in column 3 of Figure 1.
