1. Introduction to Human Genetic Epidemiology
2. Data Analysis Using R Programming
3. Applied Statistics for Human Genetics Using R
4. Applied Human Genetic Epidemiology
5. Human Genetic Epidemiology Using R
The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solve problems in quantitative Genetic Epidemiology
Biostatistics for Human Genetic Epidemiology provides statistical methodologies and R recipes for human genetic epidemiologic problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related human genetic epidemiology, with R codes illustrations for various examples.
This clear and concise book covers human genetic epidemiology, using R in data analysis, including multivariate data analysis. It examines probabilistic and statistical theories for modeling human genetic epidemiology – leading the readers through an effective epidemiologic model, from simple to advanced levels. Classical mathematical, probabilistic, and statistical theory are thoroughly discussed and presented. This book also presents R as a calculator and using R in data analysis.
Additionally, it covers Advanced Human Genetic Data Concepts, the Study of Human Genetic Variation, Manhattan Plots, as well as the Procedures for Multiple Comparison. Numerous Worked Examples are provided for illustrations of concepts and real-life applications.
Biostatistics for Human Genetic Epidemiology is an ideal reference for professionals and students in Medicine (particularly in Preventive Medicine and Public Health Medical Practices), as well as in Genetics, Epidemiology, and Biostatistics.
• Correlates with modern genetics in medicine
• Provides a current working knowledge of genetic epidemiology
• Describes statistical methods for quantitative assessment of genetic influences on diseases
• Focuses on research study designs for discovering disease susceptibility genes
• Introduces the use of the popular open-sourced computer programming language, R, for needed quantitative assessment in epidemiologic analysis
Dr. Bertram K. C. Chan is a Lecturer at the Loma Linda University of Health in the Deparment of Epidemiology and Biostatistics. He has extensive knowledge is this field and has experience writing on this subject.