CMChecker

https://github.com/whpress/cmchecker
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### Build Genealogy Tree in C++

Source: https://context7.com/whpress/cmchecker/llms.txt

This snippet demonstrates how to initialize a genealogy object, create individuals, define parent-child relationships to construct family trees, and set genome resolution for analysis.

```cpp
#include "cMchecker_body.h"

// Initialize genealogy with default 3000 genome bins
Genealogy gg;

// Create founding individuals (no parents specified)
gg.newPerson("John");
gg.newPerson("Mary");
gg.newPerson("Robert");
gg.newPerson("Susan");

// Create children with both parents
gg.newChild("Alice", "John", "Mary");
gg.newChild("Bob", "Robert", "Susan");

// Create child with one known parent (other parent anonymous)
gg.newChild("Charlie", "Alice");

// Create descendant N generations removed
gg.newChild("David", "John", 3);  // great-grandchild of John

// Change genome resolution (bins per genome)
setresolution(5000);  // higher resolution for more accuracy

```

--------------------------------

### Process Genealogy Data from Input Files (C++)

Source: https://context7.com/whpress/cmchecker/llms.txt

This snippet demonstrates how to process genealogy and data from input files for batch analysis using the cMchecker command-line interface. It covers file handling, parsing commands, and executing operations on a Genealogy and DataSet object. Compilation instructions are provided.

```cpp
// Input file format (example.txt):
// # Comments start with hash
// newPerson John
// newPerson Mary
// newChild Alice John Mary
// personOfInterest Alice Bob Charlie
// runTrials 10000
// newData Alice Bob 850.5
// showModel
// showModelOmitting Bob
// showModelMoving Alice Bob
// permanentlyRemove Charlie
// setError 0.05
// makeGED output.ged
// done

// Main program execution
int main(int argc, char **argv) {
    Genealogy gg;
    DataSet dd(gg);

    FILE *INP = fopen(argv[1], "rb");
    if (!INP) {
        printf("Cannot open file: %s\n", argv[1]);
        return 1;
    }

    // Parse and execute commands from file
    for (;;) {
        int result = parse(gg, dd, INP);
        if (result != 1) break;
    }

    fclose(INP);
    return 0;
}

// Compile and run
// g++ cMchecker.cpp -o cMchecker
// ./cMchecker input.txt

```

--------------------------------

### Run Monte Carlo Simulations in C++

Source: https://context7.com/whpress/cmchecker/llms.txt

This snippet shows how to execute Monte Carlo simulation trials to generate theoretical DNA sharing distributions. It covers specifying persons of interest, running trials with different parameter sets, and accessing the simulation results.

```cpp
// Specify persons of interest for analysis
char* persons[] = {"Alice", "Bob", "Charlie", "David", NULL};

// Run 10000 simulation trials
TrialsOutput trials = gg.runtrials(10000, persons);

// Alternative: run with separate candidate and match lists
char* candidates[] = {"Alice", "Bob", NULL};
char* matches[] = {"Charlie", "David", NULL};
TrialsOutput trials2 = gg.runtrials(5000, candidates, matches);

// Access simulation results
int ntrials = trials[0].ncols();
int npeople = trials.size();
double simulated_cm = trials[0][1][500];  // person 0 vs 1, trial 500

// Display simulation summary
printf("Ran %d trials for %d persons\n", ntrials, npeople);

```

--------------------------------

### Statistical Model Evaluation in C++

Source: https://context7.com/whpress/cmchecker/llms.txt

This code illustrates how to compare simulated DNA sharing distributions with measured data using a multivariate statistical model. It involves setting measurement error, creating a baseline model, displaying results, testing alternative hypotheses by omitting data, and comparing models via likelihood ratios and chi-square probabilities.

```cpp
// Set measurement error (default 0.03, range ~0.01-0.10)
Doub measerr = 0.03;

// Create baseline statistical model
MultivariateModel baseline(gg, trials, dd, measerr);

// Display model results with chi-square and likelihood
baseline.showmodel();
/* Example output:
   0: (Alice        Bob         ) model=0.515+-0.045 (2200-2900 cM) data=0.512 (2250 cM) pct=0.480 tval=-0.7
   1: (Alice        Charlie     ) model=0.708+-0.003 (6800-7200 cM) data=0.707 (6800 cM) pct=0.505 tval=-0.3
   ... 
   model ChiSquare = 8.52 (8.90) with DoF=12 ChiSquareProbability = 0.7435
*/

// Test alternative hypothesis by omitting problematic person
DataSet dd_test(dd);
dd_test.omit("Bob");
MultivariateModel alt_model(gg, trials, dd_test, measerr);
alt_model.showmodel();

// Compare models via likelihood ratios
double likelihood_ratio = pow(10.0, alt_model.logprob - baseline.logprob);
double chisq_ratio = alt_model.chisqprob / baseline.chisqprob;
printf("Likelihood ratio: %.4g\n", likelihood_ratio);
printf("Chi-square probability ratio: %.4g\n", chisq_ratio);

```

--------------------------------

### Advanced Genome Analysis with Low-Level Structures (C++)

Source: https://context7.com/whpress/cmchecker/llms.txt

This snippet showcases advanced genome analysis capabilities in cMchecker, allowing access to low-level chromosome and haplotype structures. It covers initializing genomes, simulating mating, calculating DNA sharing, manipulating haploid structures, performing recombination, accessing run statistics, displaying genome representations, and exporting trees to GEDCOM format.

```cpp
// Initialize with specific resolution
setresolution(3000);

// Create and manipulate genomes
Genome person1, person2;
person1.initgenome(0);  // Initialize as founder
person2.initgenome(1);

// Simulate mating
Genome child = person1.mate(person2);

// Calculate shared DNA between genomes
double shared_cm = person1.match(person2);
printf("Shared DNA: %.1f cM\n", shared_cm);

// Access haploid structures
Haploid maternal = child.mo;
Haploid paternal = child.fa;

// Perform recombination
Haploid recombined = maternal.recombine(paternal);

// Get run statistics for ancestor tracking
VecInt runs = child.fa.stats(2);  // Track ancestor ID 2
int total_segments = child.fa.stats3(2);  // Count segments

// Display genome representation
child.showgenome();
/* Output shows chromosome segments:
   (0+1)
   0000000000|111111100000|...  (father's chromosomes)
   1111111111|000000011111|...  (mother's chromosomes)
*/

// Export tree to GEDCOM format
gg.makeGED("family_tree.ged");

```

--------------------------------

### Add Genetic Match Data in C++

Source: https://context7.com/whpress/cmchecker/llms.txt

This code demonstrates adding measured DNA sharing values (in centiMorgans) between individuals to a dataset linked to a genealogy. It includes adding new pairs, updating existing data, marking zero matches, removing individuals, and moving data between names.

```cpp
// Create dataset linked to genealogy
DataSet dd(gg);

// Add pairwise DNA sharing data (values in centiMorgans)
dd.addpair("Alice", "Bob", 850.0);      // Full siblings ~850 cM
dd.addpair("Alice", "Charlie", 1700.0);  // Parent-child ~1700 cM
dd.addpair("Bob", "Charlie", 425.0);     // Aunt-nephew ~425 cM
dd.addpair("David", "Alice", 212.0);     // Great-aunt ~212 cM

// Mark person as zero-match with all others
dd.addpair("Unknown", "Alice", 0.0);
dd.addpair("Unknown", "Bob", 0.0);

// Update existing data value
dd.addpair("Alice", "Bob", 875.0);  // Overwrites previous 850.0

// Remove person from dataset
dd.omit("Unknown");

// Move one person's data to another
dd.moveto("OldName", "NewName");

```
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