The RZooRoH package
1 Installation | 2 Citations | 3 The multiple HBD classes model | 3.1 The hidden Markov model with two classes (HBD vs non-HBD) | 3.2 Extending to multiple HBD classes | 3.3 Estimating HBD probabilities and identifying HBD segments with an HMM | 3.4 Model and results interpretation | 4 Differences with other approaches | 4.1 Some differences with window-based approaches identifying ROH | 4.2 Benefits of using multiple HBD classes | 5 Input data | 5.1 Input data quality filtering | 5.2 Data format and conversion from PED or VCF files | 5.2.1 Fields for marker information | 5.2.2 Fields for genotype / sequence information | 5.2.3 Examples for the six data formats | 5.2.4 Converting from ped or VCF files | 5.3 Reading the data | 5.3.1 Specifying the data file and genotype / sequence format | 5.3.2 Specifying the format for marker information | 5.3.3 Minimal allele frequency threshold | 5.3.4 Estimation of alleles frequencies - the EM algorithm | 5.3.5 Additional external files (sample names and allele frequencies) | 5.3.6 The haploid option | 5.3.7 Structure of the zooin object | 5.4. Comment on data filtering | 6 Defining the model | 6.1 Models with one HBD class and one non-HBD class: \texttt{1L} model | 6.2 Models without pre-defined rates: \texttt{KL} models (\texttt{RZooRoH} will estimate the rates $R_k$) | 6.3 Models with pre-defined rates: \texttt{MixKL} models | 6.3.1 Selecting the number of classes and their rates | 6.3.2 Benefits of using pre-defined rates | 6.4 Using \texttt{zoomodel} to define your model | 6.4.1 Options | 6.4.2 More advanced options: stepfunctions and layers defined as intervals | 6.4.2.1 Step functions | 6.4.2.2 Layers defined as intervals | 6.4.3 Output: the \texttt{zmodel} object | 6.4.4 Some examples of model definition with \texttt | 7 Running \texttt | 7.1 General options | 7.2 Parameter estimation | 7.2.1 Methods for parameter estimation | 7.2.2 Options for parameter estimation | 7.2.3 Examples | 7.3 Estimating realized autozygosity (with partitioning in different HBD classes) | 7.4 Identifying HBD segments | 7.5 Estimation of identy-by-descent (IBD) between two phased haplotypes | 7.6 More efficient computation when \texttt | 7.7 More examples | 8 Description of results | 8.1 Parameters (likelihood and convergence) | 8.2 Realized autozygosity per class | 8.3 Defining inbreeding coefficients (with respect to a base population) | 8.4 Local HBD probabilities | 8.5 HBD segments | 8.6 Accessor functions (easier access to slots) | 8.6.1 For realized autozygosity | 8.6.2 For inbreeding coefficients | 8.6.3 For HBD segments | 8.6.4 For local HBD probabilities (locus specific) | 8.6.5 Using accessor functions with the IBD analysis | 8.6.6 Combining accessor functions with standard summary functions | 8.6.7 Merging and updating zres objects | 9 Plotting | 9.1. Proportion of the genome associated with different HBD classes (population) | 9.2. Proportion of the genome associated with different HBD classes (individuals) | 9.3. Partitioning individual genomes in different HBD classes | 9.4. Plotting identified HBD segments | 10 Impact of data quality and informativity - some caution with whole genome sequecing and reduced representation sequecing | 11 Predicting HBD in future offspring and kinship estimation with \texttt | 11.1 Running the model | 11.2 Output | 11.3 Specific accessor function
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