User: gstone2

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gstone20
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Posts by gstone2

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Comment: C: limma: how to use pairing and adjust for covariates
... I am implementing the design you've recommended and am concerned that I am not getting the contrast I am interested in. The columns Male.post and Female.post in my design matrix have a 1 for all male and female samples, respectively, taken post condition. When I contrast these, Female.post-Male.post ...
written 7 months ago by gstone20
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Comment: C: limma blocking and including covariates
... Thank you for all the help!   ...
written 7 months ago by gstone20
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Comment: C: limma blocking and including covariates
... Thank you for your elaboration--it's made me think much more. I am looking at the change in gene expression due to condition within each sex and between the sexes (f.post-f.pre)-(m.post-m.pre), so I am comparing across patients. I get the sense from your explanation that it doesn't hurt to add the c ...
written 7 months ago by gstone20
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Comment: C: limma blocking and including covariates
... Thank you for the great explanation! ...
written 7 months ago by gstone20
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limma blocking and including covariates
... I have received extraordinary help on this website, and while I have learned a lot about limma, I am still a beginner and am trying to overcome certain limitations. I am trying to determine the effect of a condition within and between the sexes, and one limitation is that I do not feel comfortable i ...
limma paired samples limma voom written 7 months ago by gstone20 • updated 7 months ago by Ryan C. Thompson6.1k
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Comment: C: limma: how to use pairing and adjust for covariates
... Ok great. Thank you very much for all of your help! ...
written 7 months ago by gstone20
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Comment: C: limma: how to use pairing and adjust for covariates
... Ok thank you, that makes a lot of sense. So just that I am clear, in both cases, sexMale_conditionpost represents the log-fold change from pre to post in males? ...
written 7 months ago by gstone20
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Comment: C: limma: how to use pairing and adjust for covariates
... So in the case when my design matrix is ~ patient + sex:condition, I should remove the pre terms from the design and then construct my contrast matrix: makeContrasts(sexDiff = "sexFemale_conditionpost - sexMale_conditionpost", levels=design) Now, in the case when my design matrix is ~ 0 + patient + ...
written 7 months ago by gstone20
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Comment: C: Limma: paired multifactor analysis
... Great, thank you. Yes, nested is a factor. However, since I have an uneven amount of males and females it is my understanding that I should remove columns from the design matrix that do not correspond to a sample. Am I correct in thinking this?   ...
written 9 months ago by gstone20
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Comment: C: Limma: paired multifactor analysis
... I apologize, I am answering from a different account since I seem to have reached a positing limit. Nested is numbering each sample within its sex group, as recommended by the edgeR manual in the section detailing making comparisons between and within groups. I would like to use limma to contrast t ...
written 9 months ago by gstone20

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