Principles of Statistical Genomics - Xu, Shizhong; SpringerLink (Online service) (New York, NY : Springer New York : Imprint: Springer, 2013)
Genetic Linkage Map -- Map Functions -- Physical map and genetic map -- Derivation of map functions -- Haldane map function -- Kosambi map function -- Recombination Fraction -- Mating designs -- Maximum likelihood estimation of recombination fraction -- Standard error and significance test -- Fisher's scoring algorithm for estimating -- EM algorithm for estimating -- Genetic Map Construction -- Criteria of optimality -- Search algorithms -- Exhaustive search -- Heuristic search -- Simulated annealing -- Branch and bound -- Bootstrap confidence of a map -- Multipoint Analysis of Mendelian Loci -- Joint distribution of multiple locus genotype -- BC design -- F2 design -- Four-way cross design -- Incomplete genotype information -- Partially informative genotype -- BC and F2 are special cases of FW -- Dominance and missing markers -- Conditional probability of a missing marker genotype -- Joint estimation of recombination fractions -- Multipoint analysis for m markers -- Map construction with unknown recombination fractions -- Basic Concepts of Quantitative Genetics -- Gene frequency and genotype frequency -- Genetic effects and genetic variance -- Average effect of allelic substitution -- Genetic variance components -- Heritability -- An F2 family is in Hardy-Weinberg equilibrium -- Major Gene Detection -- Estimation of major gene effect -- BC design -- F2 design -- Hypothesis tests -- BC design -- F2 design -- Scale of the genotype indicator variable -- Statistical power -- Type I error and statistical power -- Wald-test statistic -- Size of a major gene -- Relationship between W-test and Z-test -- Extension to dominance effect -- Segregation Analysis -- Gaussian mixture distribution -- EM algorithm -- Closed form solution -- EM steps -- Derivation of the EM algorithm -- Proof of the EM algorithm -- Hypothesis tests -- Variances of estimated parameters -- Estimation of the mixing proportions -- Genome Scanning for Quantitative Trait Loci -- The mouse data -- Genome scanning -- Missing genotypes -- Test statistics -- Bonferroni correction -- Permutation test -- Piepho's approximate critical value -- Theoretical consideration -- Interval Mapping -- Least squares method -- Weighted least squares -- Fisher scoring -- Maximum likelihood method -- EM algorithm -- Variance-covariance matrix of ˆθ -- Hypothesis test -- Remarks on the four methods of interval mapping -- Interval Mapping for Ordinal Traits -- Generalized linear model -- ML under homogeneous variance -- ML under heterogeneous variance -- ML under mixture distribution -- ML via the EM algorithm -- Logistic analysis -- Example -- Mapping Segregation Distortion Loci -- Probabilistic model -- The EM Algorithm -- Hypothesis test -- Variance matrix of the estimated parameters -- Selection coefficient and dominance -- Liability model -- EM algorithm -- Variance matrix of estimated parameters -- Hypothesis test -- Mapping QTL under segregation distortion -- Joint likelihood function -- EM algorithm -- Variance-covariance matrix of estimated parameters -- Hypothesis tests -- Example -- QTL Mapping in Other Populations -- Recombinant inbred lines -- Double haploids -- Four-way crosses -- Full-sib family -- F2 population derived from outbreds -- Example -- Random Model Approach to QTL Mapping -- Identity-by-descent (IBD) -- Random effect genetic model -- Sib-pair regression.-  Maximum likelihood estimation -- EM algorithm -- EM algorithm under singular value decomposition -- Multiple siblings -- Estimating the IBD value for a marker -- Multipoint method for estimating the IBD value -- Genome scanning and hypothesis tests -- Multiple QTL model -- Complex pedigree analysis -- Mapping QTL for Multiple Traits -- Multivariate model -- EM algorithm for parameter estimation -- Hypothesis tests -- Variance matrix of estimated parameters -- Derivation of the EM algorithm -- Example -- Bayesian Multiple QTL Mapping -- Bayesian regression analysis -- Markov chain Monte Carlo -- Mapping multiple QTL -- Multiple QTL model -- Prior, likelihood and posterior -- Summary of the MCMC process -- Post MCMC analysis -- Alternative methods of Bayesian mapping -- Reversible jump MCMC -- Stochastic search variable selection -- Lasso and Bayesian Lasso -- Example: Arabidopsis data -- Empirical Bayesian QTL Mapping -- Classical mixed model -- Simultaneous updating for matrix G -- Coordinate descent method -- Block coordinate descent method -- Bayesian estimates of QTL effects -- Hierarchical mixed model -- Inverse chi-square prior -- Exponential prior -- Dealing with sparse models -- Infinitesimal model for whole genome sequence data -- Data trimming -- Concept of continuous genome -- Example: Simulated data -- Microarray Differential Expression Analysis -- Data preparation -- Data transformation -- Data normalization -- F-test and t-test -- Type I error and false discovery rate -- Selection of differentially expressed genes -- Permutation test -- Selecting genes by controlling FDR -- Problems of the previous methods -- Regularized t-test -- General linear model -- Fixed model approach -- Random model approach -- Hierarchical Clustering of Microarray Data -- Distance matrix -- UPGMA -- Neighbor joining -- Principle of neighbor joining -- Computational algorithm -- Other methods -- Bootstrap confidence -- Model-Based Clustering of Microarray Data -- Cluster analysis with the K-means method -- Cluster analysis under Gaussian mixture -- Multivariate Gaussian distribution -- Mixture distribution -- The EM algorithm -- Supervised cluster analysis -- Semi-supervised cluster analysis -- Inferring the number of clusters -- Microarray experiments with replications -- Gene Specific Analysis of Variances -- General linear model -- The SEM algorithm -- Hypothesis testing -- Factor Analysis of Microarray Data -- Background of factor analysis -- Linear model of latent factors -- EM algorithm -- Number of factors -- Cluster analysis -- Differential expression analysis -- MCMC algorithm -- Classification of Tissue Samples Using Microarrays -- Logistic regression -- Penalized logistic regression -- The coordinate descent algorithm -- Cross validation -- Prediction of disease outcome -- Multiple category classification -- Time-Course Microarray Data Analysis -- Gene expression profiles -- Orthogonal polynomial -- B-spline -- Mixed effect model -- Mixture mixed model -- EM algorithm -- Best linear unbiased prediction -- SEM algorithm -- Monte Carlo sampling -- SEM steps -- Quantitative Trait Associated Microarray Data Analysis -- Linear association -- Linear model -- Cluster analysis -- Three-cluster analysis -- Differential expres -- SEM algorithm -- MCMC algorithm -- Joint analysis of all markers -- Multiple eQTL model -- SEM algorithm -- MCMC algorithm -- Hierarchical evolutionary stochastic search (HESS).
Keywords: Plant genetics; Animal genetics; Plant Genetics and Genomics; Animal Genetics and Genomics