January 2024

Hardy-Weinberg – Applied

Here is a problem to illustrate how the Hardy-Weinberg Principle is applied.

In a population of 130,000 special mice, green fur is dominant over orange. If there are 300 orange mice in the population of 130,000, find the following:
Frequency of green allele
Frequency of orange allele
Frequency of each genotype

p + q = 1
p2 + 2 pq + q2 = 1

We must start with orange as it is the recessive one. It is because, from the dominant (green) colour, it is impossible to say that it is homozygous dominant or heterozygous. Whereas only homozygous recessive has orange fur.

q2 = 300/130,000 = 0.0023
q = sqrt(q2) = 0.048
p = 1 – q = 0.95

Genotype Frequencies:
homozygous dominant = p2 = 0.90
Heterozygous = 2pq = 0.0456 = 0.091
Homozygous recessive = q2 = 0.0023

Reference

The Hardy-Weinberg Principle: Watch your Ps and Qs: ThePenguinProf

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Hardy-Weinberg – Continued

We have seen the terms allele, dominant, recessive, genotype, phenotype, etc. Consider a population with five individuals with the following gene pairs. Assume they dictate the hair colour. So, the red gene is for red hair colour and black for black. But red is recessive, and black is dominant. That means.

red-red = red hair
red-black = black hair
black-black = black hair

So we have two people with red hair (homozygous recessive) and three with black hair (two heterozygous and one homozygous dominant).

Hardy Weinberg rule

The rule states that allele and genotype frequencies in a population will remain constant in the absence of other evolutionary processes such as migration, mutation, selection, etc.

To estimate the allele frequency, we create the gene pool, the aggregate of all alleles of the population. Our gene pool has ten alleles, with six reds and four blacks.

Let p represent the allele frequency of the dominant trait and q that of the recessive.
p = 4/10 = 0.4
q = 6/10 = 0.6
p + q = constant = 1

To estimate genotype frequency, consider the following. If we take one random gene from the pool, what is the probability that it is red? It will be q. What is the chance of picking two genes to form a homozygous recessive? It will be q x q = q2. Similarly, to pull out a black followed by another black is p2 and a black and a red is 2pq (black followed by red OR red followed by black; add them because of OR rule).

The genotype frequency is the sum of those three types, i.e., p2 + 2 pq + q2. Needless to say, that will be 1. To summarise, the following are the two governing equations.

p + q = 1
p2 + 2 pq + q2 = 1

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Hardy-Weinberg Principle

We have two copies of every gene; each copy is called an allele. If both copies of alleles are the same, it’s homozygous. On the other hand, if they are different, it’s heterozygous. The terms dominant and recessive mean two different inheritance patterns of traits.

Imagine hair colour as a trait. The dominant is black, and the recessive is red. Note this doesn’t mean black hair dominates or anything like that. It only means:

black allele + black allele = black trait
black allele + red allele = black trait
red allele + red allele = red trait

Simply put, you need both the recessive alleles to get a recessive trait, whereas one dominant allele is sufficient to get the dominant trait.

Also, the allele pairs (black, black), (black, red) and (red, red) are all genotypes. On the other hand, the traits – black hair and red hair are two phenotypes. If a genotype is what your genes are, then a phenotype is what you look like!

Before Hardy and Weinberg, people used to get puzzled by the fact that the population did not end up having only the dominant traits. Their principle (developed independently) states that frequencies of alleles and genotypes in a population will remain constant over time in the absence of other evolutionary influences.

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Chance of DMD

A woman who has a family history of Duchenne muscular dystrophy (DMD) gets tested for the presence of disease using a test (creatine phosphokinase, CPK) that has a sensitivity of 67% and a specificity of 95%. It is known that her brother has the condition. What is the probability that she is a carrier of the condition, and further, what is the chance that her son will have the disease if she tests negative in the CPK?

The conditional probability of disease, given the negative test result. We will use Bayes’ theorem to estimate the probability.

P(C|-ve) = \frac{P(-ve|C) P(C)}{P(-ve|C) P(C) + P(-ve|nC) P(nC)}

P(C|-ve) denotes the probability that she is a carrier (C), given she tested negative for the conditions (-ve).

P(-ve|C) is the chance of a negative result, given the person is a carrier. We know the chance of a +ve results if the person carries the gene. It is the sensitivity and is 67%. This means if the person carries a gene, there is a 67% chance of getting a positive and a 33% chance of getting a negative result. Therefore, P(-ve|C) = 0.33.

P(-ve|nC) is the chance of a negative result, given the person is NOT a carrier. It is nothing but specificity, and it is 95%. Therefore, P(-ve|nC) = 0.95.

This leaves the final two parameters: the prior probabilities that she carries or does not carry the disease genes (P(C) and P(nC)). DMD happens because of a mutated gene on the X chromosome. In our case, the woman can get that X chromosome from her father or mother. Since her brother had the conditions, and he could get X only from his mother, the mother is certainly a carrier of the mutated gene. Since the daughter inherited one of two Xs from her mother, P(C) = 0.5, which means P(nC) is 0.5.

Applying the Bayes’ theorem,

P(C|-ve) = \frac{0.33*0.5}{0.33*0.5 + 0.95*0.5} = 0.26

If she is a carrier (there is a 26% chance), she could pass one of her X chromosomes to her son at a 50% chance. This implies that the probability that her son gets the disease is 0.26 x 0.5 = 0.13 or 13%.

Reference

Bayesian Analysis and Risk Assessment in Genetic Counseling and Testing: Journal of Molecular Diagnostics, Vol. 6, No. 1, February 2004

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The Advanced One

Which is the most advanced form of life?

Before we reach the answer, we must know that evolution is not a linear process (like a ladder), unlike what Aristotle thought, but a branched (like a tree). Consider the family of Apes. The apes (Hominoidea) branches into two families – the ‘great apes’ and the ‘lesser apes’.

The lesser apes contain a bunch of gibbons. The great apes are further divided into two – Homininae and orangutans.

Does this picture mean the orangutans and homininae are higher than the gibbons? No, and the scheme can also be drawn in the following way.

Homininae goes to gorillas and hominini. In other words, the gorillas and the hominini have a common ancestor. Hominini then goes to pan (chimpanzees and bonobos) and humans.

You may conclude that an advanced species goes from left to right. That is also not true. The picture can also be like this.

All these living lineages have the same amount of time to evolve; therefore, they are equal!

Reference

Ape: Wiki

Understanding Evolution: Berkeley

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Genetic Drift

We have seen natural selection as one mechanism of evolution. To clarify the whole process, this way of evolution involves two steps: 1) a random (accidental) modification of genes (mutation), followed by 2) a proliferation of a certain kind because it somehow fits well with its environment (natural selection).

But natural selection is not the only mechanism for evolution. Another means of evolution is genetic drift. In such cases, there could be no features of the genetically different versions of the species that have advantages or disadvantages from the environment. Still, random fluctuation causes one of the gene types (allele) to reduce its frequency. This also suggests that this feature is especially significant in small, isolated populations.

To give a (silly) example to distinguish the two types of evolution, we have seen the story of A moth named Biston betularia earlier. The survival probability of the black-coloured moths was higher in the industrialised (coal-polluted!) England. This is an example of natural selection. Now, think about a small population of 20 moths – 15 white and five yellows in a bright, normal neighbourhood. Someone accidentally stepped over the group, perishing seven whites and all (5) yellows. We know neither species had a special trait to withstand the boots. Yet, in the end, only eight whites were the only survivors. They then increased to a large group of white moths.

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Value of a Portfolio

What are the expected return and standard deviation of an equal-weight portfolio of two assets, A and B, with the following characteristics?

Expected return of A = 10%
Expected return of B = 5%
Standard deviation of A = 20%
Standard deviation of B = 15%
The correlation between A and B is 0.5

The expected return of the portfolio,
E[rp] = E[0.5 rA + 0.5 rB]
E[rp] = 0.5 E[rA] + 0.5 E[rB]
E[rp] = 0.5 x 0.1 + 0.5 x 0.05 = 0.075 = 7.5%

The standard deviation of the return
To calculate the standard deviation, std, we first calculate the variance, std2.
var[rp] = var[0.5 rA + 0.5 rB]
var[rp] = 0.52 x var[rA] + 0.52 var[rB] + 2 x 0.5 x 0.5 cov[A,B]
cov[A,B] = corr(A,B) x stdA x stdB
var[rA] = stdA2
var[rB] = stdB2
var[rp] = 0.52 x stdA2 + 0.52 x stdB2 + 2 x 0.5 x 0.5 corr(A,B) x stdA x stdB
var[rp] = 0.52 x 0.22 + 0.52 x 0.152 + 2 x 0.5 x 0.5 x 0.5 x 0.2 x 0.15
var[rp] = 0.023125
stdrp = sqrt(var[rp]) = sqrt(0.023125) = 0.152 = 15.2%

The portfolio’s expected return is midway between the lower and the higher; the risk (the standard deviation) is closer to the lower.

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Value of a Lottery

A lottery has the following three prizes and sells 2 million tickets
1) one bumper prize of 1 million dollars.
2) 100 first prizes of 10,000 dollars each.
3) 10,000 consolation prizes of 1 dollar each.

If one ticket costs 2 dollars, should you buy the ticket?

The answer to this question depends on two aspects.
A) The difference between the expected value and cost of a single ticket.
B) The risk appetite of the buyer.

Expected value of a ticket

EV = P(1,000,000) x 1,000,000 + P(10,000) x 10,000 + P(1) x 1
where P(1,000,000) is the probability of winning a million dollar = 1 / 2,000,000

EV = [1/2,000,000] x 1,000,000 + [100/2,000,000] x 10,000 + [10,000/2,000,000] x 1
= 1.005

The cost of a ticket ($2) is higher than the expected value of winning ($1). A risk-averse or a risk-neutral person would avoid it.

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Conditional Probabilities

Based on the following data, what is the probability of a person making no error in her tax returns without support from a tax advisor?

50% of individuals get help from a tax advisor to file their returns. The probability of an individual making an error in the tax return is 25%. The chance of the person making an error, given a tax advisor is helping, is 10%.

Let P(M|A) be the probability of not making the error, given an advisor is not helping.
Based on the Conjunction Rule,
P(M & A) = P(A) x P(M|A)
P(M|A) = P(M & A) / P(A)

P(A) = probability of no advisor
P(M & A) = joint probability of no error AND no advisor.

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Decision Quality

Sound decisions are core to achieving good outcomes. Decision quality (DQ) is the quality of a decision at the point it is made, regardless of its outcome. A decision framework should meet six requirements to reach DQ.

Appropriate frame: is about solving the right problem using the right people. The decision must have clarity of purpose, scope, boundaries and a conscious perspective.

Create doable alternatives: Give good choices within the frame. It will involve creativity, doability, breadth and completeness.

Relevant, reliable information: It may come from data and judgment. The issue with decision-making is that it is forward-looking, and all we have is data from the past. That means the data must be reliable and should describe the underlying uncertainties and biases.  

Clear values and tradeoffs: Focus on value creation and transparency of value matrix and tradeoffs.

Sound reasoning: Use the information for each alternative and get the one with the greatest value.

Commitment to action: During the decision process, it’s important to get the right people and resolve any conflicts. Quality is defined by the support across stakeholders and a team that is ready to take action.

Reference

An Introduction to Decision Quality: Strategic Decisions Group

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