A comprehensive introduction to modern applied statistical genetic
data analysis, accessible to those without a background in molecular
biology or genetics.
Human genetic research is now relevant beyond biology, epidemiology, and
the medical sciences, with applications in such fields as psychology,
psychiatry, statistics, demography, sociology, and economics. With
advances in computing power, the availability of data, and new
techniques, it is now possible to integrate large-scale molecular
genetic information into research across a broad range of topics. This
book offers the first comprehensive introduction to modern applied
statistical genetic data analysis that covers theory, data preparation,
and analysis of molecular genetic data, with hands-on computer
exercises. It is accessible to students and researchers in any
empirically oriented medical, biological, or social science discipline;
a background in molecular biology or genetics is not required.
The book first provides foundations for statistical genetic data
analysis, including a survey of fundamental concepts, primers on
statistics and human evolution, and an introduction to polygenic scores.
It then covers the practicalities of working with genetic data,
discussing such topics as analytical challenges and data management.
Finally, the book presents applications and advanced topics, including
polygenic score and gene-environment interaction applications, Mendelian
Randomization and instrumental variables, and ethical issues. The
software and data used in the book are freely available and can be found
on the book's website.
