# What is the conversion between r and FST?

We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

From Schonman (2013):

… allele A can only invade under Hamilton's condition R=$$F_{ST}$$ > C/B.

From Harpending (2002):

The best general definition of the coefficient of relation $$R_{XY}$$ between individuals X and Y is (Bulmer, 1994) $$R_{XY}$$ = $$F_{XY}$$/$$F_{XX}$$, where $$F_{XY}$$ is the kinship between X and Y and $$F_{XX}$$ is the kinship of X with himself [… ]

[… ] $$F_{ST}$$ is just the coefficient of kinship between members of the same deme [… ]

[… ] $$F_{Self} = frac{(1 + F_{ST})}{2}$$ [… ]

This means, unless I am mistaken, that if I take Harpending's equation and substitute $$F_{ST}$$ for $$F_{XY}$$ and substitute 1/2(1+$$F_{ST}$$) for $$F_{XX}$$, I can calculate within-deme relatedness: 2*$$F_{ST}$$/(1+$$F_{ST}$$).

Yet Schonman says R=$$F_{ST}$$?

What am I doing wrong here?

I am very unsure but here are my thoughts…

We can work out from

\$\$R_{XY} = F_{XY}/F_{XX}\$\$

I do not really understand the concept of coefficient of kinship and the concept of coefficient of kinship with oneself but you say

According to the paper, kinship with himself is 0.5 in a sexual population

So, let's assume

\$\$R_{XY} = 2F_{XY}\$\$

Let's assume that the individual`Y`is drawn from anywhere in the total population. Again, I don't really understand the concept of coefficient of kinship but let's assume that \$F_{XY}\$ is the same as the probability of identity by descent between these two individuals, then in Nei (1973) terms, \$F_{XY} = J_T = 1 - H_T\$. Hence, \$R_{XY} = 2left(1 - H_T ight)\$ or \$H_T = 1-frac{R_{XY}}{2}\$

Given that

\$\$F_{ST} = 1 - frac{H_S}{H_T}\$\$

it results that

\$\$H_T = frac{H_S}{1-F_{ST}}\$\$

and therefore,

\$\$1-frac{R_{XY}}{2} = frac{H_S}{1-F_{ST}}\$\$

solving into

\$\$R_{XY} = frac{ 1 - frac{H_S}{1-F_{ST}} }{2} = frac{1-F_{ST} - H_T}{2(1-F_{ST})}\$\$

I would recommend you making some more reading on the coefficient of kinship to ensure that my interpretation here is correct.

I am not very at ease with the concepts of coefficient of kinship but

if \$F_{self} = F_{XX}\$, then

\$\$R_{XY} = 2F_{XY}(1 + F_{ST})\$\$

Assuming that`Y`is a random individual from the total population and if \$F_{XY}\$ is the probability of identity by descent of haplotypes`X`and`Y`(which I am unsure because I don't really ), then \$F_{XY} = H_T\$ and hence

\$\$R_{XY} = 2H_T(1 + F_{ST})\$\$

But really I am very unsure about all that. Note also that the small calculation is based upon the equation \$F_{Self}\$ = 1/2(1 + \$F_{ST}\$, which I don't really understand! I would recommend you making some more reading on the coefficient of kinship to ensure that my interpretation here is correct.

## Metapopulation

A metapopulation consists of a group of spatially separated populations of the same species which interact at some level. The term metapopulation was coined by Richard Levins in 1969 to describe a model of population dynamics of insect pests in agricultural fields, but the idea has been most broadly applied to species in naturally or artificially fragmented habitats. In Levins' own words, it consists of "a population of populations". [1]

A metapopulation is generally considered to consist of several distinct populations together with areas of suitable habitat which are currently unoccupied. In classical metapopulation theory, each population cycles in relative independence of the other populations and eventually goes extinct as a consequence of demographic stochasticity (fluctuations in population size due to random demographic events) the smaller the population, the more chances of inbreeding depression and prone to extinction.

Although individual populations have finite life-spans, the metapopulation as a whole is often stable because immigrants from one population (which may, for example, be experiencing a population boom) are likely to re-colonize habitat which has been left open by the extinction of another population. They may also emigrate to a small population and rescue that population from extinction (called the rescue effect). Such a rescue effect may occur because declining populations leave niche opportunities open to the "rescuers".

The development of metapopulation theory, in conjunction with the development of source–sink dynamics, emphasised the importance of connectivity between seemingly isolated populations. Although no single population may be able to guarantee the long-term survival of a given species, the combined effect of many populations may be able to do this.

Metapopulation theory was first developed for terrestrial ecosystems, and subsequently applied to the marine realm. [2] In fisheries science, the term "sub-population" is equivalent to the metapopulation science term "local population". Most marine examples are provided by relatively sedentary species occupying discrete patches of habitat, with both local recruitment and recruitment from other local populations in the larger metapopulation. Kritzer & Sale have argued against strict application of the metapopulation definitional criteria that extinction risks to local populations must be non-negligible. [2] : 32

Finnish biologist Ilkka Hanski of the University of Helsinki was an important contributor to metapopulation theory.

## Temperature Unit Conversion Formulas

There's no complicated math required to convert one temperature unit to another. Simple addition and subtraction will get you through conversions between the Kelvin and Celsius temperature scales. Fahrenheit involves a bit of multiplication, but it's nothing you can't handle. Just plug in the value you know to get the answer in the desired temperature scale using the appropriate conversion formula:

Kelvin to Celsius: C = K - 273 (C = K - 273.15 if you want to be more precise)

## Examples of Conversion Factors

There many different types of measurements that sometimes require conversions: length (linear), area (two dimensional) and volume (three dimensional) are the most common, but you can also use conversion factors to convert mass, speed, density, and force. Conversion factors are used for conversions within the imperial system (feet, pounds, gallons), within the International System of Units (SI, and the modern form of the metric system: meters, kilograms, liters) or across the two.

Remember, the two values must represent the same quantity as each other. For example, it's possible to convert between two units of mass (e.g., grams to pounds), but you generally can't convert between units of mass and volume (e.g., grams to gallons).

Examples of conversion factors include:

## Conversion

n. a civil wrong (tort) in which one converts another's property to his/her own use, which is a fancy way of saying "steals." Conversion includes treating another's goods as one's own, holding onto such property which accidently comes into the convertor's (taker's) hands, or purposely giving the impression the assets belong to him/her. This gives the true owner the right to sue for his/her own property or the value and loss of use of it, as well as going to law enforcement authorities since conversion usually includes the crime of theft. (See: theft)

## Important Definitions in research

The margin of error is the amount of accuracy you need. That is the plus or minus number that is often reported with an estimated percentage and can also be referred to as the confidence interval. It’s the range where the true population ratio is estimated to be and is frequently expressed in percentage points (e.g., ±2 percent ). Be aware after you collect your information will probably be more or less than this goal sum because it’ll be dependent upon the proportion rather than your sample percentage that the precision achieved.

The confidence level is the probability that the proportion that is true is contained by the margin of error. In case the study was repeated and each time was calculated by the range, you’d expect the true value to lie inside these ranges on 95 percent of events. The higher the confidence level, the more certain you can be that the interval includes the true ratio.

This is the entire number of individuals on your population. In this formula, we use a finite population correction to account for sampling from populations that are small. But you do not know how large you are able to use 100,000 if your population is big. The sample size does not change considerably for people larger.

The sample proportion is what you expect the outcomes to be. This can often be set using the results in a survey, or by running small pilot research. Use 50%, which gives the most significant sample size and is conservative, if you are uncertain. Notice that this sample size calculation uses the Normal approximation to the Binomial distribution. In the event, the sample ratio is close to 1 or 0, then this approximation is not valid, and you want to take into account an alternative sample size calculation method.

Here is the minimum sample size you need to gauge the true population ratio. Note that if some people choose not to respond if non-response is a chance and that they cannot be contained in your sample, your sample size is going to need to be increased. Generally, the higher the response speed, the better the quote will lead to biases in your quote.

## What is the difference between Transformation and Conjugation ?

1. It is a process of genetic recombination in bacteria where DNA fragments are taken up by bacterial cells from external medium.

2. Here direct contact between bacterial cells does not occur.

3. Only small fragments of DNA are taken up.

4. This occurs in bacterium.

### Conjugation

1. It is also a process of genetic recombination in bacteria, where two cells conjugate and a segment of DNA transfers from one another.

2. Here two bacterial cells come in contact and a conjugation tube is formed.

3. An appreciable length of DNA segment can be transferred.

4. This involves two strains of bacteria.

### Related posts:

PreserveArticles.com is an online article publishing site that helps you to submit your knowledge so that it may be preserved for eternity. All the articles you read in this site are contributed by users like you, with a single vision to liberate knowledge.

## What is Transversion

A transversion is another type of base substitution in which a particular base from class coverts into a base in the other class. That means the purines convert into pyrimidines, and pyrimidines convert into purines. Here, due to the presence of two types of purines and pyrimidines, the base subjected to the conversion has two possibilities. However, since the ring structure is going to be changed, transversions are less frequent in the genome.

Figure 2: Point Mutations

Furthermore, the effect of a transversion in the genome is more pronounced since it can alter the type of amino acid in a polypeptide chain. For example, transversions in the third base of a codon lead to the degeneracy of the codon, resulting in a different amino acid in the polypeptide chain.

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and Docker images.

• BioconductorBioc 3.13 Released.
• Bioconductorbrowsable code base now available.
• See our google calendar for events, conferences, meetings, forums, etc. Add your event with email to events at bioconductor.org.
• BioconductorF1000 Research Channel is available.
• Orchestrating single-cell analysis with Bioconductor (abstract website) and other recent literature.