Different statistical analysis in different experiments in a project
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7.5 years ago

hi , I have several RNAseq experiments in a project . In the step of filtering , in one experiment t-test gives appropriate number of genes , in another one, Beggerly test gives suitable number of genes and t-test doesn't answer . It makes me confused . Is it possible that in a project we use different types of statistical analysis in its different experiments? my experiments have repetition . thanks,

RNA-Seq • 1.4k views
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What are you testing with t-tests and beggerly tests? What do you aim to achieve and how are you running the tests?

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Dear Fatemeh, Hi

Are you intend to perform some DEG analysis? it is not clear that what is the purpose of using t-test. are you comparing for example the FPKM of some candidate gene in this way (which I guess it is not a correct approach)?

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Dear Farbod,

I don't intend to compare the FPKM, I have some experiments for treatment case and some for control case, differential expression genes are manifold , I want to reduce them , I am filtering with Fold change and Pvalue , there are three types of Pvalue according to three test that I run on my data,(I mean t-test,DEG,Baggerley test).Now I want to choose among them .

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Have you tried FDR as a filtering threshold?

By the way, I do not get the point why you are trying to reduce your DEGs?

Are you already know the answer of your investigation ?

~ Take care

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Do you mean "Baggerly's test" (i.e., this)? I thought that was essentially a beta-binomial, which wouldn't normally be appropriate (the distribution is annoying to fit properly to begin with).

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Dear Devon, thanks for your reply , I couldn't find this, Is it possible to compare these three tests( Baggerley , t-test , DEG) with each other? I need a brief explanation about them.

thanks

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I assume that you're using CLC. If so, call them and ask them to give you a short writeup on this. You're paying them already, so they'll tell you what you need to know.

Also, I don't know what "DEG" would be in this context. Normally that's "differentially expressed genes", but that's not any particular test.

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