Reciprocal Cross Outcome Shift

Compare reciprocal-cross phenotype distributions without asserting sex linkage from a difference alone.

Description

Reciprocal crosses exchange parental roles while retaining the phenotype categories.

Reciprocal crosses exchange parental roles while retaining the phenotype categories. Comparing their distributions reveals an observed shift that may have several causes.

Compare reciprocal-cross phenotype distributions without asserting sex linkage from a difference alone.

When to use Reciprocal Cross Outcome Shift

Use this for the following task: Compare reciprocal-cross phenotype distributions without asserting sex linkage from a difference alone.

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

How to use Reciprocal Cross Outcome Shift and understand its results

Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
Enter phenotypeLabels, firstCrossCounts, reciprocalCrossCounts using the field table, then run the tool.
Read firstPercentages, reciprocalPercentages, differencePoints. 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
phenotypeLabels	Phenotype labels	list of string; each entry: string	Required
firstCrossCounts	First cross counts	list of number; each entry: number	Required
reciprocalCrossCounts	Reciprocal cross counts	list of number; each entry: number	Required

Align phenotype labels and nonnegative counts for both crosses, requiring a positive total in each. Normalize independently to percentages and subtract category by category.^[1]

differencePoints = reciprocalPercentage − firstPercentage

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

Output field	Meaning	Value type
firstPercentages	First percentages	list of number
reciprocalPercentages	Reciprocal percentages	list of number
differencePoints	Difference points	list of number

json

{
  "input": {
    "phenotypeLabels": [
      "affected",
      "unaffected"
    ],
    "firstCrossCounts": [
      20,
      80
    ],
    "reciprocalCrossCounts": [
      40,
      60
    ]
  },
  "output": {
    "firstPercentages": [
      20,
      80
    ],
    "reciprocalPercentages": [
      40,
      60
    ],
    "differencePoints": [
      20,
      -20
    ]
  }
}

Limitations and assumptions

A difference alone does not establish sex linkage or statistical significance.

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 X Dominant Daughter Evidence for this operation: Audit affected-father daughter observations against a fully penetrant X-dominant model. 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

Reciprocal Cross Outcome Shift — tool.io

Similar or alternative tools

X Dominant Daughter Evidence
Audit affected-father daughter observations against a fully penetrant X-dominant model.
Phenotype Class Aggregation
Aggregate genotype-class probabilities into caller-defined phenotype percentages.