Examples

            Chapter 1
            #  1.1:  Identifying the minor allele and its frequency

        


            Chapter 2

            

            #  2.1: Chi-squared test for association
            #  2.2: Fisher's exact test for association
            #  2.3: Chochran-Armitage (C-A) trend test for association
            #  2.4: Two-sample tests for association for a quantitative trait

  
        
            #  2.5: M-sample tests of association for a quantitative trait
            #  2.6: Linear Regression

         

            Chapter 3

            #  3.1: Measuring LD using D-prime 
            #  3.2: Measuring LD for a group of SNPs

            #  3.3: Measuring LD based on r^2 and the \chi^2-statistic
            #  3.4: Determining average LD across multiple SNPs

            #  3.5: Population substructure and LD
            #  3.6: Testing for HWE using Pearsons \chi^2-test

            #  3.7:  Testing for HWE using Fishers exact test
            #  3.8:  HWE and geographic origin

            #  3.9: Generating a similarity matrix
            #  3.10: Multidimensional scaling (MDS) for identifying population substructure

            #  3.11: Principal components analysis (PCA) for identifying population substructure 

            Chapter 4

            #  4.1: Bonferroni adjustment
            #  4.2: Tukeys single-step method
 

            #  4.3: Banjamini and Hochberg (B-H) adjustment

            #  4.4: Benjamini and Yekutieli (B-Y) adjustment

            #  4.5: Calculation of the q-value

            #  4.6: Free step down resampling adjustment

            #  4.7: Null unrestricted bootstrap approach

            Chapter 5
            #  5.1: EM approach to haplotype frequency estimation

            #  5.2: Calculating posterior haplotype probabilities 
            #  5.3: Testing hypotheses about haplotype frequencies within the EM framework

            #  5.4: Application of haplotype trend regression (HTR)
            #  5.5: Multiple imputation for haplotype effect estimation and testing

            #  5.6: EM for estimation and testing of haplotype-trait association

            Chapter 6
            #  6.2: Creating a classification tree

            #  6.3: Generating a regression tree
            #  6.4: Categorical and ordinal predictors in a tree
            #  6.5: Cost-complexity pruning
      

                            

            Chapter 7
            #  7.1: An application of random forests

            #  7.2: RF with missing SNP data - single imputation
            #  7.3: RF with missing SNP data - multiple imputation

            #  7.4: MIRF

            #  7.5: Application of logic regression

            #  7.6: Monte Carol logic regression

            #  7.7: An application of MARS




      

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