R package to plan animal breedings: sample size calculation with the probability of success and offspring genotypes parameters
library(devtools)
devtools::install_github("VladaMilch/breedingCalculator")
When the breeding set up is aimed at offsprings of a single genotype, or simply a total number of born pups, one may use the following function to calculate the required number of breedings.
Here we calculate how many FVB/N mouse matings are required to ensure that at least 20 pups are born within a period of 3 days, with the success probability of 90%.
n_breedings_single <- singleGenotype(
confidence_p = 0.90,
birth_days = 3,
n_offsprings = 20,
sex_distribution = "unimportant",
desired_genotype_p = 0.25,
strain = "FVB/N")
print(n_breedings_single)
Note that in the example above, both male and female pups are suitable for the breeding experiment.
In case an experiment requires the same number of male and female pups,
one can use the following input:
sex_distribution = "balanced".
In case all pups must be male or all female,
use sex_distribution = "all one sex".
n_breedings_single <- singleGenotype(
confidence_p = 0.90,
birth_days = 3,
n_offsprings = 20,
sex_distribution = "balanced",
desired_genotype_p = 0.25,
strain = "FVB/N")
print(n_breedings_single)
Assume we breed +/- and +/- mice. According to Mendel law (Punnett square), the probabilities of offsprings +/+, +/- and -/- are 25%, 50% and 25%. We only need 10 pups of -/- genotype, and require them to be born within a perios of 3 days.
Further, we want all pups to be of one and the same sex (either male or female).
Lastly, we want to ensure that the above requirements are met in at least 95 out of 100 trials (on average).
n_breedings_multi <- multiGenotype(
confidence_p = 0.95,
birth_days = 30,
genotypes_N = c(0,0,10),
genotypes_p = c(0.25, 0.5, 0.25),
sex_distribution = "all one sex",
strain = "FVB/N",
litter_average = 6)
n_breedings_multi
str(n_breedings_multi)
How many animals (in total) should be expected to be born with the breeding setup from above?
expectBorn(n_breedings_multi)
How does the cofidence change based on the number of matings we execute? Maybe, there is a more optimal choice? Especially relevant for small breedings.
probabilitiesPlots(n_breedings_multi)