variance decomposition formula
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Xinwei • 0
@bca21fe5
Last seen 19 months ago
United States

Hi,

I am sorry that I was not able to find the correct way to type in the math formula directly. Thus, I typed the question in Latex/Overleaf and added it as an image below. Thanks a lot for the help!

Best regards,

Xinwei

enter image description here

edgeR • 1.3k views
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@gordon-smyth
Last seen 13 hours ago
WEHI, Melbourne, Australia

Your formula agrees with that in the edgeR documentation.

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Thanks, Gordon! Doesn't the formula in edgeR user guide have u intead of E(u) on the right side? Or do I misunderstand the notation?

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\mu_{gi} is a constant, not a random variable. See the Methods and Materials section of

McCarthy, DJ, Chen, Y, Smyth, GK (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 40, 4288-4297. https://doi.org/10.1093/nar/gks042

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Thanks for the paper! I still do not understand why \mu_{gi} is a constant. As each biological replicate i has a different \mu_{gi}, \mu_{gi} seems to be a random variable. The Methods and Materials section of paper also mentions "treating the \pi_{gi} as gamma distributed". Since \mu_{gi} = N_{i} * \pi_{gi}, if \pi_{gi} is gamma-distributed random variable, why is \mu_{gi} a constant?

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The first display equation in the Materials and Methods section is slightly misleading. It should read

E(y_{gi}) = \mu_{gi} = N_i E(\pi_{gi})

We should perhaps have introduced a new symbol for E(\pi_{gi}), but the paper already has a lot of mathematics for an article in the NAR journal.

The \mu_{gi} only differ between replicates if N_i varies.

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Thanks a lot, Gordon! I think I understand it now. In this definition, \mu_{gi} is indeed a constant w.r.t. \pi_{gi}.

In addition to the paper you mentioned above and other papers cited in edgeR user guide, are there any other sources (e.g. a book chapter or a video lecture) showing the step-by-step breakdown of the math behind edgeR?

Thanks again!

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