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Thread: Statistical Test for fold changes of gene expression

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    Statistical Test for fold changes of gene expression




    Hi everyone,

    I am currently doing my masters and working on gene expression in tumor and control animals. I am really lost when it comes to the right statistical tests and hope you can help me.
    I meassure the expression in a specific cell type and (for simplicity) just have two groups: "control" and "tumor". I repeated the experiment 4 times - always with littermates from the same mother, half of which got a tumor and half did not. I use quantitative RT PCR and a delta delta Ct calculation which gives me fold changes in the end.
    So in the end i get something like this:
    Control: 1 , 1 , 1 , 1
    Tumor: 14 , 50 , 30 , 100

    My questions are the following:
    - Do i have a paired or unpaired observation here?
    Each mouse is a different animal but i matched them so I can compare between the two groups and I calculate the fold change for each experiment so they have to be seen together (1 and 14, 1 and 50, etc)?

    - Which statistical test could I use to show that I always have a strong induction of gene expression in the tumor group?
    The high variation gives me no statistical significance with a paired t-test but I'm not sure I'm allowed to use that one.
    A colleague suggested a Mann-Whitney-U Test but I'm not sure either whether I am allowed to use that one here.

    I would be really glad I you could give me some suggestions!

    Thanks a lot in advance!
    biba

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    Re: Statistical Test for fold changes of gene expression

    I suggest Mann-Whitney-U Test for your data.

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    Re: Statistical Test for fold changes of gene expression

    Thank you for your fast reply.
    As far as I understand Mann-Whitney-U is for unpaired data - is that the case for my "fold change" data? Since one column is always expressed relatively to the other one.

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    Re: Statistical Test for fold changes of gene expression

    hi,
    I am not sure that the prerequisites apply, but maybe you could try a two-way ANOVA? One factor could be treated or not treated, the other the litter. So, you could isolate the effect of the litter.

    The fact that anpaired t did not give you a significant result is not a good sign though.

    regards
    rogojel

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    Re: Statistical Test for fold changes of gene expression


    This is next generation sequencing data right? Are you only interested in a single gene or are you going to be running this test for multiple genes?
    I don't have emotions and sometimes that makes me very sad.

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