Quantitative Genetics

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Genetic analysis of complex characteristics

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Quantitative genetics

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Characteristics that vary continuously along a scale of measurements with many overlapping phenotypes

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Continuous characteristics

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Are traits that are influenced by genes at many loci

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Polygenic

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Characteristics thatare both polygenic and influenced by environmental factors

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Multifactorial

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The relationship of phenotype and genotype is straightforward, each genotype produces a single phenotypeand most phenotyprs encoded by a single genotype

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Discontinuous characteristics

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The same genotype may produce a range of potential phenotypes which may overlap

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Continuous characteristics

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Types of quantitative characteristics

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Meristic and threshold

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Not continous but are determined by multiple genetic and environmental factors and has a limited number of phenotypes

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Meristic characteristics

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Measured by presence or absenxe, exhibit only two phenotypes but are determined by multiple genetic environmental factors

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Threshold characterisric

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Underlying susceptibility

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Liability or risk

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A graph of the frequencies of the different phenotyped

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Frequency distribution

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X axis expresses?

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Phenotypic classes

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Y axis expresses?

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Numbers of individuals in each class

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Group of interest

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Population

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Smaller collection of individuals

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Sample

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Characteristics of a good sample

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Must be representative, must be large enough

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Determining sample size

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Determine the margin error, determine the confidence level

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This is the positive and negative deviation you allow in your results for the sample, the deviation of each individual and the population

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Margin error

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The probability that the result lies within the boundaries of the margin error

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Confidence level

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Indicates the variability of a group of measuremebts or how spread bout the disteibution

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Variance

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Also called the average and provides information about the center of the distribution

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The Mean

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Often preferred for describing the variability of a measurement

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Standard deviation

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Used to describe the shape of the norma distribution

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Mean and standard deviation

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Is a probability function that describes how the values of a variable is distributed

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Normal distribution

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Provides a quick estimate of the spread of data in a normal distribution given the mean snd standard deviation.

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Emprical rule, three sigma rule, 68-95-99.7 rule

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When a number of data points fall outside the three standard eviation range.

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Rough gauge of normality

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A measure used to represent how strongly two random variables are related

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Correlation

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A measure used to indicate the extent to which two random varaibles chsnge in tandem

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Covariance

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Referred to the scale form of variance

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Correlation

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Is a measurement correlation

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Covariance

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Is a statistical measure that calculates the strength of the relationshio between the relative movements of two variables

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Correlation coefficient

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There js a direct association between variables

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Positive value

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There js an inverse association between variables

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Negative value

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No association between values

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Zero value

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Allows to predict the characteristics of offsleing from a giiven mating, even wjthout the knowledge of the genotypes

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Regression

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Indicates how much y increases on average per increase in x

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Regression coefficient

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Defines the relation between the x and y variables

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Regression line