User: Yogender Gowtham

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Posts by Yogender Gowtham

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Comment: C: Design matrix for unbalanced data
... Thanks Aaron. Well, So my first question had two factors - cell type and nutrient level. But you had suggested the grouping the factors together (which, if I understand correctly, has turned the model into a one-factor layout). Now, just so I understand clearly, are you also suggesting that I use t ...
written 3.8 years ago by Yogender Gowtham20
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Comment: C: Design matrix for unbalanced data
... Hello I keep coming back with more questions. Could you please help me understand how and why a one-way design layout is statistically equivalent to a 2-factor or a 3-factor design matrix? It would be helpful if you could point out some kind of reference or a paper. How does the layout change when ...
written 3.8 years ago by Yogender Gowtham20
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Comment: C: Design matrix for unbalanced data
... Hello Aaron Thank you once again for your answers. I have some questions related to this experimental setup. I would like to pursue an unbalanced 2-factor ANOVA analysis to look at the differential genes involved in the main effects of treatment and cell type along with interaction. I know you ment ...
written 3.8 years ago by Yogender Gowtham20
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Comment: C: Design matrix for unbalanced data
... My apologies. I didn't notice the add comment button. And Yes, you're right about the Intercept. It should say groupP_A. Thanks ...
written 3.8 years ago by Yogender Gowtham20
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Answer: A: Design matrix for unbalanced data
... Thanks Aaron. I actually had another design where it is same as you have suggested. Please correct me if I am wrong.  design <- model.matrix(~0+group) rownames(design) <- samples$file design colnames(design) #[1] "groupP_A" "groupP_B" "groupX_C" "groupX_A" "groupX_B" #For interaction ...
written 3.8 years ago by Yogender Gowtham20 • updated 3.8 years ago by Gordon Smyth39k
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Design matrix for unbalanced data
... Hello All Is this the correct design matrix for the following experiment? The experiment has a Normal cell line (P) and a Mutant cell line (X) that were grown with decreasing nutrient levels, A, B, and C.  A is represent 100% nutrient for a particular component, B represent 50% , and C represents 0 ...
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Comment: C: Setting up the Design Matrix
... Hello Yushun, could you please elaborate how the above contrast to find the main effect of temperature work?  Thanks ...
written 3.9 years ago by Yogender Gowtham20
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Comment: C: Setting up the Design Matrix
... Hello Yushun, could you please elaborate how the above contrast to find the main effect of temperature work?  Thanks ...
written 3.9 years ago by Yogender Gowtham20
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Comment: C: Setting up the Design Matrix
... It is quite possible that my contrast was setup wrongly with the simpler one-way layout.  I saw your comments on how interpreting coef=3 as main effect can be misleading. So I suppose there is no way of knowing the main effect given the presence of interaction terms. So coef=3 gives me the DGE due ...
written 3.9 years ago by Yogender Gowtham20
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Comment: C: Setting up the Design Matrix
... Thank you once again. The discussion in that post was informative. I do now understand the differences in estimating the differentially expressed genes was due to higher degrees of freedom available for the earlier model mentioned where I am just looking at the main effects. Now, through the latter ...
written 3.9 years ago by Yogender Gowtham20

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Popular Question 3.7 years ago, created a question with more than 1,000 views. For Setting up the Design Matrix

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