RNA-seq data analaysis: probability of making at least one type I error

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Homework Help Overview

The discussion revolves around the analysis of RNA-seq data, specifically focusing on the probability of making at least one type I error in hypothesis testing. Participants are exploring the relationship between the number of tests conducted and the probability of type I errors, particularly in the context of true null hypotheses.

Discussion Character

  • Exploratory, Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants discuss the formula for calculating the probability of at least one type I error and the significance of the variable m0, which represents the number of true null hypotheses. Questions arise regarding the interpretation of m0 and its relationship to the total number of tests.

Discussion Status

The discussion is active, with participants clarifying definitions and exploring the implications of different variables in the context of the problem. Some guidance has been provided regarding the interpretation of m0 and its distinction from the total number of tests.

Contextual Notes

Participants are working with a specific problem set, and there is an indication that earlier questions may not be necessary for the current focus on question D. The clarity of terminology and definitions is a point of contention.

Hamsi
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Homework Statement
I need to derive a mathematical expression for the probability of making at least one type I error. In this expressrion i need to use the number of true null hypothesis m0.

Also the number of genes is p and the number of tests is m.
Relevant Equations
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In general the probability of getteing at least one type I error is P=1-(1-a)^m. With m being the number of tests and a the probabiliy of getting a type I error. But i do not know how to get an expression with m0
 
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Hamsi said:
i need to use the number of true null hypothesis .
Please explain what that means. Can you post the whole question as given to you?
 
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Thank you for looking at my question! This is the entire problem set. I got stuck on question D. The previous questions (a-c) are not neceassy for question D, Ithink. I would appreciate anything the can get me a step further.
 
Ok, I think I understand. They are defining m0 as the number of tests, out of all the tests conducted, for which the null hypothesis is true; i.e. these are the ones that ought not be rejected. Calling it the "number of true null hypothesis " is just poor English.
The m in the formula you quote is the same thing. It is not the total number of tests.
If you wanted a formula based on the total number of tests you would need to plug in a value for the proportion of tests in which the null hypothesis is correct.
E.g. if the null hypothesis were false in every case then the probability of a type I error in the batch would be zero.
 
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That makes sense. Thank you very much!
 

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