26. Many different mutations (>1500 to date) in the CFTR gene can cause Cystic Fibrosis (CF). The disease shows allelic heterogeneity and many CF sufferers are compound heterozygotes i.e. they have two different mutations, one in each of their copies of the CFTR gene. -1 in 25 people in Australia are carriers for CF (an autosomal recessive disease). DNA ests are used to detect CF mutations in carriers but it is too expensive to test, or screen for all mutations so only the most common mutations are tested for. A typical CF carrier screen s 90% accurate, i.e. 10% of mutations are missed by the screen. a. Use Bayesian Analysis to calculate the probability that a woman who: a) has no family history of CF; and b) tests negative (negative means no mutation is found) on a mutation screen, is a carrier. Provide answers to 3 decimal places. Scenario A woman is a carrier Scenario B woman is not a carrier Prior Probability Cond. Probability Joint probability Posterior probability b. If this woman's partner is a known carrier for CF, the probability that the couple's first child will have CF (to three decimal places):

Biology (MindTap Course List)
11th Edition
ISBN:9781337392938
Author:Eldra Solomon, Charles Martin, Diana W. Martin, Linda R. Berg
Publisher:Eldra Solomon, Charles Martin, Diana W. Martin, Linda R. Berg
Chapter16: Human Genetics And The Human Genome
Section16.3: Genetic Diseases Caused By Single-gene Mutations
Problem 7LO: State whether each of the following genetic defects is inherited as an autosomal recessive,...
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Q6. Many different mutations (>1500 to date) in the CFTR gene can cause Cystic Fibrosis
(CF). The disease shows allelic heterogeneity and many CF sufferers are compound
heterozygotes i.e. they have two different mutations, one in each of their copies of the CFTR
gene. ~1 in 25 people in Australia are carriers for CF (an autosomal recessive disease). DNA
tests are used to detect CF mutations in carriers but it is too expensive to test, or screen for
all mutations so only the most common mutations are tested for. A typical CF carrier screen
is 90% accurate, i.e. 10% of mutations are missed by the screen.
a. Use Bayesian Analysis to calculate the probability that a woman who: a) has no family
history of CF; and b) tests negative (negative means no mutation is found) on a mutation
screen, is a carrier. Provide answers to 3 decimal places.
Scenario A woman is a
Scenario B woman is not a
carrier
carrier
Prior Probability
Cond. Probability
Joint probability
Posterior probability
b. If this woman's partner is a known carrier for CF, the probability that the couple's first child
will have CF (to three decimal places):
Transcribed Image Text:Q6. Many different mutations (>1500 to date) in the CFTR gene can cause Cystic Fibrosis (CF). The disease shows allelic heterogeneity and many CF sufferers are compound heterozygotes i.e. they have two different mutations, one in each of their copies of the CFTR gene. ~1 in 25 people in Australia are carriers for CF (an autosomal recessive disease). DNA tests are used to detect CF mutations in carriers but it is too expensive to test, or screen for all mutations so only the most common mutations are tested for. A typical CF carrier screen is 90% accurate, i.e. 10% of mutations are missed by the screen. a. Use Bayesian Analysis to calculate the probability that a woman who: a) has no family history of CF; and b) tests negative (negative means no mutation is found) on a mutation screen, is a carrier. Provide answers to 3 decimal places. Scenario A woman is a Scenario B woman is not a carrier carrier Prior Probability Cond. Probability Joint probability Posterior probability b. If this woman's partner is a known carrier for CF, the probability that the couple's first child will have CF (to three decimal places):
Q7. With multifactorial disorders, several genes (as well as environmental factors) are
contributing to the disease therefore Mendel's Laws cannot be used as anterior information to
calculate risk figures. In such cases, empiric recurrence risk is used to estimate the likelihood
of a disease occurring. These figures are calculated by comparing the incidence of a disease
in close relatives of an affected individual (familial incidence) to the frequency of the disease
in the general population (population incidence).
Chance of
Chance of affected
Population
incidence
unaffected parents
having a 2nd
affected child
parents having an
affected child
(%)
Disorder
(%)
(%)
Cleft lip/palate
0.1-2
4
Congenital heart
0.8
1.4
2(father), 6(mother)
defect
Spina bifida
0.25
4-5
4
Schizophrenia
10
14
a. Using the information provided in the table above (and from previous questions), rank the
following events in order of probability, from most likely to least likely: a) parents of a child
with cleft palate having a second child with same disease; b) someone with no family
history of the disease developing schizophrenia; c) parents of a child with thalassemia
having a second child with thalassemia; d) a woman with a congenital heart defect having
a child with the same condition.
b. An unaffected couple have one child with both cleft lip and congenital heart defects.
Assuming that these two disorders are NOT related, what is the probability that this couple
will have a second child with BOTH these disorders (to five decimal places)? Show your
calculation.
Transcribed Image Text:Q7. With multifactorial disorders, several genes (as well as environmental factors) are contributing to the disease therefore Mendel's Laws cannot be used as anterior information to calculate risk figures. In such cases, empiric recurrence risk is used to estimate the likelihood of a disease occurring. These figures are calculated by comparing the incidence of a disease in close relatives of an affected individual (familial incidence) to the frequency of the disease in the general population (population incidence). Chance of Chance of affected Population incidence unaffected parents having a 2nd affected child parents having an affected child (%) Disorder (%) (%) Cleft lip/palate 0.1-2 4 Congenital heart 0.8 1.4 2(father), 6(mother) defect Spina bifida 0.25 4-5 4 Schizophrenia 10 14 a. Using the information provided in the table above (and from previous questions), rank the following events in order of probability, from most likely to least likely: a) parents of a child with cleft palate having a second child with same disease; b) someone with no family history of the disease developing schizophrenia; c) parents of a child with thalassemia having a second child with thalassemia; d) a woman with a congenital heart defect having a child with the same condition. b. An unaffected couple have one child with both cleft lip and congenital heart defects. Assuming that these two disorders are NOT related, what is the probability that this couple will have a second child with BOTH these disorders (to five decimal places)? Show your calculation.
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