This unique volume is the first to cover a wide range of design and analysis issues in genetic studies of rare variants, with contributions from experts in the field, through large-scale international consortia including the UK10K Project, GO-T2D and T2D-GENES. The book presents state-of-the-art methodology for rare variant detection and calling, imputation, and analysis in samples of unrelated individuals and families. It also covers analytical issues associated with the study of rare variants, such as the impact of fine-scale population structure, and rare variants studies in a meta-analysis framework.
This book covers multiple aspects of study design, analysis and interpretation for complex trait studies focusing on rare sequence variation. In many areas of genomic research, including complex trait association studies, technology is in danger of outstripping our capacity to analyze and interpret the vast amounts of data generated.
The field of statistical genetics in the whole-genome sequencing era is still in its infancy, but as this book illustrates, powerful methods to analyze the aggregation of low-frequency and rare variants are now starting to emerge. The chapter Functional Annotation of Rare Genetic Variants is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
This book covers multiple aspects of study design, analysis and interpretation for complex trait studies focusing on rare sequence variation. In many areas of genomic research, including complex trait association studies, technology is in danger of outstripping our capacity to analyze and interpret the vast amounts of data generated.
The field of statistical genetics in the whole-genome sequencing era is still in its infancy, but as this book illustrates, powerful methods to analyze the aggregation of low-frequency and rare variants are now starting to emerge. The chapter Functional Annotation of Rare Genetic Variants is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
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