Meta analysis of healthy and diseased data
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5.7 years ago
chris86 ▴ 370

Hi

I am in progress of trying to understand how to combine two separate microarray experiments run on the same Illumina platform, but several months apart, run in the same lab. The problem is, that healthy individuals and diseased individuals are in the two respective batches or experiments. From what I understand this makes any accurate batch correction impossible (?).

Further, if I want to combine them, I was thinking of quantile normalising separately, then I have read on another thread to try and POE normalise separately and then combine? However, if they are completely different experiments, I think POE normalisation - which converts gene by gene to 0 to 1 probability of expression is not the right method to use.

I was also thinking of using a rank method (rankprod) to do differential expression, I guess this makes more sense, but some genes could be DE due to a batch effect still.

Is there a best or better method here? Or is this idea just a bit crazy?

Please don't ask me why it was done like this, it depresses me to think about it.

Thanks,

Chris

next-gen • 1.2k views
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Adding in a phenotype table to describe the experiment would be helpful to understand if this is an impossible, or just challenging task.

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Hello chris86!

It appears that your post has been cross-posted to another site: Bioconductor: https://support.bioconductor.org/p/83411/

This is typically not recommended as it runs the risk of annoying people in both communities.

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ok thanks i wont do that anymore

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