User: laianavarromartin

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Spain
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9 months ago
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2 years, 6 months ago
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l****************@gmail.com

Posts by laianavarromartin

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Comment: C: Extract results from DESeq2 object for base level of term of interest using LRT
... Hi Mike, when you say "which test if any level of stage has a difference"... does that refer between all levels of a factor, or between all levels against the level defined as control? ...
written 9 months ago by laianavarromartin10
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Comment: A: Similar to Tukey Post hoc after ANOVA
... Hi again, Sorry, I have another question...when I do the Walt test the adjusted pvalue is adjusted by the multiple comparisons of many genes. In the case exposed above if I have a factor with 4 levels meaning that If I do a walt test I will end up looking at 6 comparisons of levels by pairs. Should ...
written 9 months ago by laianavarromartin10
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Comment: A: LRT test multiple comparisons
... Hi Mike, First of all thanks for all your patience and time dedicated to us. I think I have been mistaken these tests all the time. I have an appointment with a local statistician hoping to help me on this...but I had in my mind that doing the Walt test was similar to a t-test, and doing a LRT was ...
written 9 months ago by laianavarromartin10
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LRT test multiple comparisons
... Hi, My question refers to the multiple comparison done by LRT test. I though that this test would compare all the levels of a factor between them, but if I'm not mismatching...it is only comparing all the levels with the one I'm considering the "control" group. This is my experimental design: ...
deseq2 extracting contrasts written 9 months ago by laianavarromartin10
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Comment: C: Multi-factorial design in DEseq2: defining reduced model
... And why do not include Dose as a factor in the design? I also want to find the genes that are altered by dose regardless of the window of exposure. On the other hand, why the walt test is better than the LRT? To make my life easier I always compare the Walt and LRT to a t-test or to an ANOVA. Does ...
written 9 months ago by laianavarromartin10
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Comment: A: Multi-factorial design in DEseq2: defining reduced model
... I have another experiment a little more complicated.  Have fish exposed to 3 different compounds at equivalent doses. I want to see which genes are specifically regulated by each compound, and which are common to all of them.  Compound Dose Rep.nested 1 Control 1 ...
written 9 months ago by laianavarromartin10
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Comment: C: Multi-factorial design in DEseq2: defining reduced model
... ok, just to make sure I understand correctly: 1. I should run the DE as  dds <- DESeqDataSet(se, design = ~window + window:rep.nested + window:dose ) dds$dose <- relevel(dds$dose, "Control") dds <- DESeq (dds) 2. Then I can extract the results for each window separately (comparing 2 d ...
written 9 months ago by laianavarromartin10
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Comment: C: Multi-factorial design in DEseq2: defining reduced model
... Mike, thanks this is clear now. ...
written 9 months ago by laianavarromartin10
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Comment: A: Multi-factorial design in DEseq2: defining reduced model
... Apart from choosing the best design, I still do not understand how should we do the LRT. So I come back to my original question: Once I define the full model, should i leave out the variable of interest in the reduced model to be looking at the DE genes that are defined by that variable? So in the ...
written 9 months ago by laianavarromartin10
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Comment: C: Multi-factorial design in DEseq2: defining reduced model
... But, animals from the R1 and R4 do not come from the same plate. Is that correct?  That means that in our case is a nested design, but Replicates from different experiments are not the same.  ...
written 9 months ago by laianavarromartin10

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