Double Crossover Coincidence
Compare observed double crossovers with independent-interval expectation and compute interference.
Description
Double-crossover coincidence compares observations with an independent-interval expectation.
Double-crossover coincidence compares observations with an independent-interval expectation. Interference is one minus that observed-to-expected ratio.
Compare observed double crossovers with independent-interval expectation and compute interference.
When to use Double Crossover Coincidence
Use this for the following task: Compare observed double crossovers with independent-interval expectation and compute interference.
Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
How to use Double Crossover Coincidence and understand its results
- Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
- Enter observedDoubleCrossovers, totalProgeny, firstIntervalRecombination, secondIntervalRecombination using the field table, then run the tool.
- Read expectedDoubleCrossovers, coefficientOfCoincidence, interference. 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 |
|---|---|---|---|
| observedDoubleCrossovers | Observed double crossovers | integer | Required |
| totalProgeny | Total progeny | integer | Required |
| firstIntervalRecombination | First interval recombination | number | Required |
| secondIntervalRecombination | Second interval recombination | number | Required |
Use nonnegative observed count no greater than positive progeny and interval fractions in [0,1]. Require a positive expected count before division.1
expected = progeny r1 r2; coincidence=observed/expected; interference=1−coincidence This summarizes the declared operation. Units, indexing, inclusivity and exceptional cases are explained in the surrounding text.
| Output field | Meaning | Value type |
|---|---|---|
| expectedDoubleCrossovers | Expected double crossovers | number |
| coefficientOfCoincidence | Coefficient of coincidence | number |
| interference | Interference | number |
{
"input": {
"observedDoubleCrossovers": 10,
"totalProgeny": 1000,
"firstIntervalRecombination": 0.1,
"secondIntervalRecombination": 0.2
},
"output": {
"expectedDoubleCrossovers": 20,
"coefficientOfCoincidence": 0.5,
"interference": 0.5
}
}Limitations and assumptions
Interference can be negative. The tool does not identify crossover classes or perform a significance test.
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 Three Point Middle Gene for this operation: Resolve the middle gene from one-locus differences between parental and double-crossover haplotypes. For a complementary task, use Linkage Interval Map for this operation: Build additive genetic-map positions from ordered adjacent interval distances.
The implementation reference documents the exact calculation, supported input shapes and returned fields.
References
-
Double Crossover Coincidence — tool.io
Similar or alternative tools
- Three Point Middle Gene
Resolve the middle gene from one-locus differences between parental and double-crossover haplotypes.
- Linkage Interval Map
Build additive genetic-map positions from ordered adjacent interval distances.