Additive Phenotype Class Count

Count equal-effect additive phenotype classes under a fully segregating diploid locus model.

Description

An equal-effect additive diploid model groups offspring by the number of contributing allele copies.

An equal-effect additive diploid model groups offspring by the number of contributing allele copies. Fully segregating loci permit counts from zero through twice the locus count.

Count equal-effect additive phenotype classes under a fully segregating diploid locus model.

When to use Additive Phenotype Class Count

Use this for the following task: Count equal-effect additive phenotype classes under a fully segregating diploid locus model.

Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.

How to use Additive Phenotype Class Count and understand its results

Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
Enter equalEffectLocusCount using the field table, then run the tool.
Read expectedPhenotypeClasses. Interpret flags, units, ordering and placeholder values using the rules below.
Review any reported issue or failed check, correct the supplied values when appropriate, and verify the result in its intended context.

Input field	Meaning	Value type and bounds	Requirement
equalEffectLocusCount	Equal effect locus count	integer	Required

Supply a positive integer number of equal-effect loci. Return the theoretical class count.^[1]

expected phenotype classes = 2 equalEffectLocusCount + 1

This summarizes the declared operation. Units, indexing, inclusivity and exceptional cases are explained in the surrounding text.

Output field	Meaning	Value type
expectedPhenotypeClasses	Expected phenotype classes	number

json

{
  "input": {
    "equalEffectLocusCount": 3
  },
  "output": {
    "expectedPhenotypeClasses": 7
  }
}

Limitations and assumptions

Complete segregation, equal effects and distinguishable phenotypes are assumed. Dominance, unequal effects and environmental variation are excluded.

The tool evaluates supplied observations or a declared model. It does not establish the biological cause of an observed pattern. Malformed requests produce input errors. A successfully evaluated request can still contain false flags, empty result lists or a result outside the supplied threshold; those outcomes have the meanings stated above.

Alternative or Complementary methods

Choose Trihybrid Gamete Grid for this operation: Enumerate three-locus Mendelian gamete combinations and distinct multilocus offspring genotypes. For a complementary task, use Phenotype Class Aggregation for this operation: Aggregate genotype-class probabilities into caller-defined phenotype percentages.

The implementation reference documents the exact calculation, supported input shapes and returned fields.

References

Additive Phenotype Class Count — tool.io

Similar or alternative tools

Trihybrid Gamete Grid
Enumerate three-locus Mendelian gamete combinations and distinct multilocus offspring genotypes.
Phenotype Class Aggregation
Aggregate genotype-class probabilities into caller-defined phenotype percentages.