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Thread: pairwise comparison regardless effect

  1. #1
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    pairwise comparison regardless effect




    Hi there,

    I want to do a pairwise comparison of gene expressions (continuous values) before and after treatment of a group of patients regardless the direction of the effect. So the genes can either show either up- or down-regulation in course of the treatment. Using normal t-statistics does not help here because up-regulation "neutralises" down-regulation and vice versa. That is why no pairwise group comparison can be made.

    So how to test the null-hypothesis of "there is no change of gene expression"?

    Please see the attached screenshot visualising the data situation.

    Many thanks!
    Attached Images  

  2. #2
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    Re: pairwise comparison regardless effect

    Are you looking for something like a test for "H0: The mean absolute change in gene expression is exactely 0 in the population"? You need not test that, you just need 1 case with absolute change > 0 to reject the null. And you have more than 1 case with abslute change > 0 here.

    With kind regards

    K.

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    bambam (04-29-2013)

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    Re: pairwise comparison regardless effect


    Hello,

    Your patient are paired, so could you substract the "after" result to the "before" result for each patient, plot the resulting values and analyse the distribution ?
    Sheldon : Well, there’s always the possibility that a trash can spontaneously formed around the letter, but Occam’s Razor would suggest that someone threw it out.

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