How to handle the data from studies of complex disease Flashcards
What does parametric linkage analysis determine?
Genetic determinants of disease.
How are parametric linkage analysis set up?
Ascertain (a small set of) large families (pedigrees) each containing a number of affected individuals
Use a genotyping technique to measure the alleles (genotype) at one or more loci, in as many individuals as are available
Examine the co-segregation (co-transmission) of disease phenotype and alleles at the genetic marker loci
What is genetic distance measured in?
Morgans (M) or centimorgan (cM)
What is the connection between Morgans and recombination?
Recombination between alleles at two loci closely related to physical distance.
What symbol represents the probability of recombination between loci?
θ (Theta)
What are the ranges of θ?
0 to 0.5
What is the value of θ when the loci lies close?
θ is small (≈0) and the loci are said to be completely linked.
What is the value of θ when the loci are further apart?
θ approaches 0.5
Loci are said to be unlinked (alleles at the two loci are transmitted independently)
What is the Likelihood ratio test?
Using a computer program to calculate the likelihood of observed genotype and phenotype data in a set of families.
What does the likelihood ratio depend on?
How well the observations match the assumed model
What is a LOD score?
Testing for linkage using likelihood ratio test.
What does the LOD score test for?
Tests the null hypothesis that the disease locus lies far away from the genotyped marker locus.
What is the null hypothesis in a LOD score test?
θ = 0.5 (unlinked)
How to calculate parametric linkage analysis (likelihood ratio)?
LRmax = L(θˆ) / L(0.5)
What is L(θˆ)?
The value of θ that maximises the likelihood (makes the data ‘most likely’ to have occurred).
How to calculate the LOD score based on the likelihood ratio?
The log base 10 of the likelihood ratio.
What is considered a “Convincing” LOD score as evidence for linkage?
3
Why is 3 a “Convincing” LOD score?
Corresponds to a likelihood ratio of 1000
Data is 1000 times more likely under the alternative hypothesis than under the null hypothesis.