| Business Data Model Data Model |
Description | An association between a population and an allele which can be used to identify the genomic statistical values that are linked to a set of subjects within a cohort. |
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Relationship | |
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Reverse Dependencies | |
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Attribute Details |
Description | The frequency of the allele in this cohort group. The allele frequency represents the incidence of a gene variant in a population. An allele frequency is calculated by dividing the number of times the allele of interest is observed in a population by the total number of copies of all the alleles at that particular genetic locus in the population. Allele frequencies can be represented as a decimal, a percentage, or a fraction. In a population, allele frequencies are a reflection of genetic diversity. Changes in allele frequencies over time can indicate that genetic drift is occurring or that new mutations have been introduced into the population. |
Data Type | Standards - Data Domains.ddm/Data Domains/Rate [FLOAT(5)] |
Is Part Of PrimaryKey | false |
Is Required | false |
Is Derived | false |
Is Surrogate Key | false |
Description | The heterozygosity or genetic diversity associated with the known Cohort samples. A measure of genetic variation in a population. For example: If an individual carries the gene for black hair and the gene for blond hair, that individual is heterozygous for hair color. Heterozygosity can also refer to the percentage of locations on a chromosome that are heterozygous in an individual. These locations are called loci (the singular form is locus) and may contain more than one gene. The concept of heterozygosity is frequently extended from an individual to a population in the study of population genetics. Heterozygosity in a population is calculated as follows: 1) pi is the frequency p of the allele that has an index number of i for a given locus. The value of pi can therefore range from 0 to 1. 2) Calculate the predicted heterozygosity for a single locus. This is given by the equation 1 - ?pi^2. Since the sum of the terms pi^2 is less than 1, heterozygosity is a value between 0 and 1. Heterozygosity can therefore be expressed as a percentage. 3) Interpret the significance for the predicted heterozygosity at a single locus. The equation the equation 1 - ?pi^2 shows that maximum heterozygosity occurs when the alleles for that locus are equally common. For example, for two equally common alleles, heterozygosity is 1 - ?pi^2 = 1 - (1/2)^2 - (1/2)^2 = 1/2. 4) Calculate the predicted heterozygosity for multiple loci. In this case, we want to find the average of the sum of the squares of the allele frequencies and subtract it from 1. Thus, heterozygosity for multiple loci is 1 - 1/m??pi^2. 5) Evaluate the observed heterozygosity of a population for a single locus. We have Ho = ?xi/n, where Ho is the observed heterozygosity, n is the population and xi is 0 if the alleles in the individual with index i are equal and 1 if they are different. |
Data Type | Standards - Data Domains.ddm/Data Domains/Rate [FLOAT(5)] |
Is Part Of PrimaryKey | false |
Is Required | false |
Is Derived | false |
Is Surrogate Key | false |
Description | The number of samples analyzed to create these statistics. |
Data Type | Standards - Data Domains.ddm/Data Domains/Number Integer [INTEGER] |
Is Part Of PrimaryKey | false |
Is Required | false |
Is Derived | false |
Is Surrogate Key | false |
Relationship Details |
Is Identifying Relationship | false |
Child Table | Population Sequence Statistics |
Child Multiplicity | ZERO_TO_MANY |
Child Referential Integrity: On Delete | NONE |
Child Referential Integrity: On Insert | NONE |
Child Referential Integrity: On Update | NONE |
Parent Table | Allele |
Parent Multiplicity | ZERO_TO_ONE |
Parent Referential Integrity: On Delete | NONE |
Parent Referential Integrity: On Insert | NONE |
Parent Referential Integrity: On Update | NONE |
Is Identifying Relationship | true |
Child Table | Population Sequence Statistics |
Child Multiplicity | ZERO_TO_MANY |
Child Referential Integrity: On Delete | NONE |
Child Referential Integrity: On Insert | NONE |
Child Referential Integrity: On Update | NONE |
Parent Table | Population |
Parent Multiplicity | ONE |
Parent Referential Integrity: On Delete | NONE |
Parent Referential Integrity: On Insert | NONE |
Parent Referential Integrity: On Update | NONE |
| Business Data Model Data Model |