User: Fischer-philipp

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Posts by Fischer-philipp

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Comment: C: DESeq2: How does the model of the trend function looks like?
... Hey Michael, Yes your support is great! I am sorry that I bothered you with my questions. All the best =). ...
written 9 weeks ago by Fischer-philipp20
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Comment: C: DESeq2: How does the model of the trend function looks like?
... Another question came to my mind. Am I getting the cox-reid adjustment right. 1/2 log det xt w x One penalized values for alpha which have a lot of information on mu? If so I do not get why this makes sense. To emphasize on values of alpha coming more from the poisson distribution? Thanks agai ...
written 9 weeks ago by Fischer-philipp20
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Comment: C: DESeq2: How does the model of the trend function looks like?
... I understand that - thank your for your help. ...
written 9 weeks ago by Fischer-philipp20
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Comment: C: DESeq2: How does the model of the trend function looks like?
... =) nice thanks. Further it would be great if you are so kind and comment my suggestion (the link) of how to derive the sigma_^2_d of the normal hierarchical. ![model of hierarchical normal with full bayes][1] https://ibb.co/xHcZ2MR [1]: https://ibb.co/xHcZ2MR ...
written 9 weeks ago by Fischer-philipp20
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Comment: C: DESeq2: How does the model of the trend function looks like?
... Hey - Thank you again. So I was trying to draw sthg like this: ![Hierarchical normal ][1] https://pasteboard.co/IdKFNpx.png Which is from: http://idiom.ucsd.edu/~rlevy/pmsl_textbook/chapters/pmsl_8.pdf ![hierarchical normal model deseq2?][2] https://pasteboard.co/IdKGGQF.jpg Does it make sense? ...
written 9 weeks ago by Fischer-philipp20
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Comment: C: DESeq2: How does the model of the trend function looks like?
... So I am wonderin what the hierarchical normal model looks like: - ) log(a_i^gw) - log(a_tr(\bar mu_i) ~ N(a_i_gw, S_lr) - ) a_i^gw ~ N(a_i; sigma^i_lde) - ) log(a_i) ~ N(log(a_tr(\bar mu_i); Sigma^2_d) as prior It is really interesting for me what you did - but I am really stuck. Thank you ag ...
written 12 weeks ago by Fischer-philipp20
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Comment: C: DESeq2: How does the model of the trend function looks like?
... Thank you very much for your very helpfull answers. Unfortunately I am stuck in the section of **Dispersion Prior:** Additional file 1: Table S2 compares: - ψ1((m−p)/2) as an approximation of σ2lde with - the variance of logarithmic Cox–Reid adjusted dispersion. And says it is very similar. A ...
written 12 weeks ago by Fischer-philipp20
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DESeq2: How does the model of the trend function looks like?
... Hello Community, The paper of DESe1 says that the forumula [(6)][1] : A parametric curve of the form (6) is fit by regressing the gene-wise dispersion estimates α_g^wi onto the means of the normalized counts, μ̄ i via a gamma-family GLM regression. Wihtin the Source code of DESeq2 I found the f ...
deseq2 gamma-family dispersion trend written 12 weeks ago by Fischer-philipp20 • updated 12 weeks ago by Michael Love24k
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Comment: C: DESeq2 - Method-of-moments - negative binomial
... Thank you for your quick answers. so it comes from the relationship sigma^2 = \mu + \alpha \mu^2 ? It still remains a question to me why it is: `(bv - xim*bm)/bm^2 }` and not `(bv - xim*bm)/(xim*bm)^2 }` or `(bv - bm)/bm^2` ...
written 3 months ago by Fischer-philipp20
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DESeq2 - Method-of-moments - negative binomial
... Within the function `momentsDisEstimate()` of `DESeq2` a rough method-of-moments estimate of the mean counts is derived by this equation `(bv - xim*bm)/bm^2 `. (I am aware that this is just an initial set to maximize Cox-Reid adjusted likelihood of the gene-wise dispersion estimat.) So I was curi ...
deseq2 method-of-moments negative binomial written 3 months ago by Fischer-philipp20 • updated 3 months ago by Michael Love24k

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