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Statistical Methods in Genetic Epidemiology

by Duncan C. Thomas

A methods-based guide to studying genes, environment, and disease

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Hardcover New English

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AlbakiReads Editorial

A methods-based guide to studying genes, environment, and disease

Organized around the progression of genetic epidemiology research, this text connects study design with statistical analysis for investigating how inherited and environmental factors relate to disease patterns. It moves from assessing familial aggregation and separating possible genetic and environmental contributions to estimating genetic models, locating implicated genes, and examining population-level effects. Examples involving breast and colorectal cancer ground the methodology in published disease research. Introductory coverage of molecular biology, Mendelian and population genetics, epidemiology, and statistics provides shared foundations across disciplines, while the central emphasis remains on the analytical tools used in genetic epidemiologic investigation.

Good fit for readers who enjoy

  • Graduate students in epidemiology, biostatistics, or human genetics
  • Researchers seeking a reference on genetic epidemiology methods
  • Learners entering the field from one of its adjacent disciplines

Themes

Gene–environment interactionGenetic epidemiologyStudy designStatistical analysisDisease patterns

Based on publisher information and book metadata.

Book overview

This well-organized and clearly written text has a unique focus on methods of identifying the joint effects of genes and environment on disease patterns. It follows the natural sequence of research, taking readers through the study designs and statistical analysis techniques for determining whether a trait runs in families, testing hypotheses about whether a familial tendency is due to genetic or environmental factors or both, estimating the parameters of a genetic model, localizing and ultimately isolating the responsible genes, and finally characterizing their effects in the population. Examples from the literature on the genetic epidemiology of breast and colorectal cancer, among other diseases, illustrate this process. Although the book is oriented primarily towards graduate students in epidemiology, biostatistics and human genetics, it will also serve as a comprehensive reference work for researchers. Introductory chapters on molecular biology, Mendelian genetics, epidemiology, statistics, and population genetics will help make the book accessible to those coming from one of these fields without a background in the others. It strikes a good balance between epidemiologic study designs and statistical methods of data analysis.
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