Probability in tests in genetics

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Homework Help Overview

The discussion revolves around probability calculations related to genetic testing, specifically focusing on the accuracy of a test that detects a gene associated with a certain protein synthesis in humans. Participants explore the implications of test sensitivity and specificity within a population context.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the application of Bayes' Theorem and consider using a hypothetical population to analyze test outcomes. There are attempts to calculate the probability of test results indicating the presence of the gene and the probability of incorrect test results.

Discussion Status

The conversation includes various attempts to calculate probabilities, with some participants providing calculations and others questioning the accuracy of their results. There is a mix of approaches being explored, and while some guidance is offered, no consensus on the final probabilities has been reached.

Contextual Notes

Participants are working with specific probabilities related to test accuracy and population prevalence, but there are indications of confusion and variability in calculations. The discussion reflects the challenges of interpreting statistical outcomes in the context of genetic testing.

Jeff_McD18
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Q. A certain gene is necessary for certain protein synthesis in human beings. A new kind of test can detect the gene in people who have the gene 99.9% of the time, and falsely detects the gene 10.3% of the time when a person does not carry the gene. 93% of the population carries the gene disease.

. What is the probability that a test result states the gene is detected?
. What is the probability the test is wrong?

I do not know how i would even attempt this question...any guidelines?
 
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Well, you might want to look into Bayes' Theorem (try Wikipedia).

An intuitive way to do it is to create a large population, and then figure out what happens to it.

So suppose there are 100,000 people. How many of them actually have the disease? Suppose we test them all. How many are correctly identified as having it? How many false positives are there? How many silent negatives are there? etc...
 


Okay! So would the probability that a rest result states the gene is detected be 0.936?
 


would work down to something like:

(99.9% x 93%) + (10.3% x 0.07%)

=0.93628 ??
 


Yes, that's right.
 


Okay sweet!

Okay what if it ask What is the probability the test is wrong...What would i do in that instance?
 


Well, take a stab at it yourself. You have all these tests (93.6% positive, the rest negative). How many of them are right?
 


I come up with 0.098, but i believe that is wrong. Other than that, I have no idea. Can you elaborate a little bit?
 


Categorize all the people into the following:

Has the gene/test says yes
Has the gene/test says no
No gene/test says yes
No gene/test says no

Figure out how many in each group. Then you should be home free to answer any questions about this test and population.
 
  • #10


The Probability that the test is wrong would then equal 0.007
 
  • #11


How'd you get that? It seems close but a little too low.
 
  • #12


i have a page full of calculations. they keep changing everytime i try something new. 0.077 is what I am getting now man any ideas?
 
  • #13


Well let's see. Someone has the gene 93% of the time, and when they do it's reported that they have it 99.9% of the time. So out of 100k people, 930 would have the gene but the test would say no.

7% of people don't have the gene, and it's reported that they do 10.3% of the time. So out of 100k people, 7000 don't have the gene, and 721 get positive test results.

So summing those, we get that 1651 people would get wrong test results if everyone were tested, or about 1.65%.
 
  • #14


awesome thanks
 

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