Question: Filtering samples or not before normalisation for samples from several groups
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gravatar for Zhilong Jia
4.6 years ago by
Zhilong Jia1.6k
London
Zhilong Jia1.6k wrote:

Is it good or not to filter non-related samples before gene expression normalisation for samples from several groups (for example, A (control), B and C; B and C are a subtype of a disease) because I focus on B Vs A; C Vs A, B Vs C and C+B Vs A. With no filtering, it will be an issue especially when comparing B Vs C, resulting in none differentially expressed genes. Thank you.

ADD COMMENTlink modified 4.6 years ago by Devon Ryan96k • written 4.6 years ago by Zhilong Jia1.6k
2
gravatar for Devon Ryan
4.6 years ago by
Devon Ryan96k
Freiburg, Germany
Devon Ryan96k wrote:

In general, keeping all of the samples/groups together during normalization is preferred. The reason is that most current methods use one form of empirical Bayes or another and you tend to get more accurate background distributions then. But of course if whatever method you use doesn't do that then the answer might be different.

ADD COMMENTlink modified 4.6 years ago • written 4.6 years ago by Devon Ryan96k
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