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An Introduction to Statistical Genetic Data Analysis 1st edition by Melinda Mills, Nicola Barban, Felix C Tropf ISBN 0262538385 9780262538381

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An Introduction to Statistical Genetic Data Analysis Melinda C. Mills Digital Instant Download

Author(s): Melinda C. Mills, Nicola Barban, Felix C. Tropf
ISBN(s): 9780262538381, 0262538385
Edition: Illustrated
File Details: PDF, 17.08 MB
Year: 2020
Language: english
SKU: EB-56576428 Category: Tags: , ,

An Introduction to Statistical Genetic Data Analysis 1st Edition by Melinda Mills, Nicola Barban, Felix C Tropf – Ebook PDF Instant Download/Delivery: 0262538385, 9780262538381
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ISBN 10: 0262538385 
ISBN 13: 9780262538381
Author: Melinda Mills, Nicola Barban, Felix C Tropf

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.

An Introduction to Statistical Genetic Data Analysis 1st Table of contents:

  1. Basic Genetics and Genomic Data:

    • Introduction to classical and molecular genetics.
    • Types of genetic data: single nucleotide polymorphisms (SNPs), copy number variation (CNV), sequencing data, etc.
    • Sources of genetic data and data formats used in statistical analysis.

  2. Descriptive Statistics for Genetic Data:

    • Basic statistical techniques used to summarize genetic data (e.g., frequency distributions, summary statistics, graphical representation).
    • Understanding linkage disequilibrium, allele frequency distributions, and genotype distributions.

  3. Statistical Models in Genetics:

    • Explanation of statistical models commonly used in genetics, such as linear models, logistic regression, and mixed-effects models.
    • Analysis of genotype-phenotype associations and genetic mapping.
    • Population genetic models and the concept of genetic inheritance.

  4. Statistical Methods for Association Studies:

    • Overview of genome-wide association studies (GWAS) and their statistical foundations.
    • Techniques for analyzing genotype-phenotype associations, including case-control studies and regression-based approaches.
    • Challenges and limitations of GWAS, including multiple testing and statistical power.

  5. Quantitative Trait Locus (QTL) Mapping:

    • The concept of QTLs and methods for mapping them.
    • Statistical tools for QTL detection, including linkage analysis and Bayesian approaches.
    • Applications of QTL mapping in plant and animal breeding.

  6. Population Genetics and Statistical Analysis:

    • Basic principles of population genetics, including Hardy-Weinberg equilibrium, genetic drift, and gene flow.
    • Statistical methods for studying population structure and evolutionary processes.
    • Approaches to estimating genetic diversity and relatedness within and between populations.

  7. Statistical Genetics of Complex Traits:

    • The role of genetics in complex traits and diseases.
    • Statistical techniques for studying complex traits, including heritability estimation, genetic interaction, and polygenic risk scores.

  8. Genetic Data Analysis Software and Tools:

    • Introduction to popular software and programming languages used in genetic data analysis (e.g., R, PLINK, STRUCTURE).
    • Practical examples of implementing statistical methods for genetic data analysis.

  9. Advanced Topics in Statistical Genetics:

  • More advanced statistical approaches, such as whole-genome sequencing analysis, epistasis, gene-environment interactions, and network analysis.
  • Discussion of emerging techniques and technologies in statistical genetics.

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Melinda Mills,Nicola Barban,Felix C Tropf,Statistical Genetic,Data Analysis