Statistical Human Genetics
Description
The aim of this volume is to make computer programs for analyzing human genetic data more easily accessible to the beginner. Statistical Human Genetics: Methods and Protocols, Second Edition provides updated and new chapters detailing genetic terms, analysis software, and how to interpret the program outputs. Written in the highly successful Methods in Molecular Biology series format, the chapters include introductions to their respective topics, step-by-step instructions, and tips on troubleshooting and avoiding known pitfalls.
The purpose of Statistical Human Genetics: Methods and Protocols, Second Edition is to ensure successful and meaningful results in the fast-growing field of genetic epidemiology.
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Content
Statistical Genetic Terminology.- Identification of Genotype Errors.- Detecting Pedigree Relationship Errors.- Identifying Cryptic Relationships.- Estimating Allele Frequencies.- Testing Departure from Hardy-Weinberg Proportions.- Estimating Disequilibrium Coefficients.- Detecting Familial Aggregation.- Estimating Heritability from Twin Studies.- Estimating Heritability from Nuclear Family and Pedigree Data.- Correcting for Ascertainment.- Segregation Analysis using the Unified Model.- Design Considerations for Genetic Linkage and Association Studies.- Model-based Linkage Analysis of a Quantitative Trait.- Model-based Linkage Analysis of a Binary Trait.- Model-free Linkage Analysis of a Quantitative Trait.- Model-free Linkage Analysis of a Binary Trait.- Single Marker Association Analysis for Unrelated Samples.- Single Marker Family-based Association Analysis Conditional on Parental Information.- Single Marker Family-based Association Analysis not Conditional on Parental Information.- Calibrating Population Stratification in Association Analysis.- Cross-phenotype Association Analysis using Summary Statistics from GWAS.- Haplotype Inference.- Multi-SNP Haplotype Analysis Methods for Association Analysis.- The Analysis of Ethnic Mixtures.- Detecting Multiethnic Rare Variants.- Identifying Gene Interaction Networks.- Structural Equation Modeling.- Mendelian Randomization.- Preprocessing and Quality Control for Whole Genome Sequences from the Illumina HiSeq X Platform.- Statistical Approaches for Processing and Analyzing Microbiome Data.
