User: Keifa

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Keifa10
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Posts by Keifa

<prev • 9 results • page 1 of 1 • next >
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Comment: C: Continuous variable interaction with Groups in design matrix
... Hi Aaron, I am sorry to revive an old thread but I have a question related to con1 and con2. I did not get the difference between the two  comparisons. coef 1 of con1 and con2 should output the same results, am I wrong?  Keifa ...
written 12 months ago by Keifa10
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Comment: C: Limma DesignMatrix, dropping terms
... Hi Aaron, I get it, thank you very much.  Keifa ...
written 13 months ago by Keifa10
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Comment: C: Limma DesignMatrix, dropping terms
... Hi Aaron, thank you for your comment. "SDF.LFD" term seems to be the reference level for factor SD and if you do not drop the coefficient 7 (you need to achieve full column rank), the three terms "SDM.LFD", "SDM.WD" and "SDF.WD" (the once dropped) should represent the log-fold change respect the re ...
written 13 months ago by Keifa10
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Comment: C: Limma DesignMatrix, dropping terms
...   Hi Aaron,  Maybe I am wrong, but this is what you wrote (https://support.bioconductor.org/p/68916/#110986): > design2 <- model.matrix(~0 + Litter + SD) > design2 <- design2[,-7] > colnames(design2) [1] "LitterL37" "LitterL39" "LitterL40" "LitterL48" "LitterL49" "LitterL50" [7] " ...
written 13 months ago by Keifa10
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Comment: C: Design and contrast question limma (additive or nested or duplicateCorrelation()
... Done: https://support.bioconductor.org/p/110987/ ...
written 13 months ago by Keifa10
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Limma DesignMatrix, dropping terms
... Hello guys,  I was surfing the blog and I stopped in this post https://support.bioconductor.org/p/68916/#110986. The guy had this experimental design: Filename Sexe Diet Litter sample1 M LFD L37 sample2 M LFD L37 sample3 M LFD L49 sample4 M LFD L49 sam ...
limma designmatrix written 13 months ago by Keifa10 • updated 13 months ago by Aaron Lun24k
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Comment: C: Design and contrast question limma (additive or nested or duplicateCorrelation()
... Hi Aaron, I have  doubt why dropping coef number 7 the final two terms represent the average log-fold change for male mice over female, in the LFD or WD-fed mice. The design matrix would be:   SDM.LFD SDM.WD Filename Sexe Diet 0 0 sample13 F LFD ...
written 13 months ago by Keifa10
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Answer: A: Re-use limma beta coefficients
... Hi Aaron, Thank you for your answer, I have really appreciated it. I did not catch your point about "differences of differences". Do you mean perform a statistical test for each gene using the two log-fold changes and confidence intervals? K  ...
written 2.7 years ago by Keifa10
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Re-use limma beta coefficients
... Dear All, I am analysing a gene expression profiling (Illumina microarray) of 12 samples, 6 of them are organoids and 6 are the matched tumor samples. The gene expression profiles of organoids and tumor samples look different and I identified hundreds of genes differentially expressed (lmfit+eBayes ...
limma removebatcheffect written 2.7 years ago by Keifa10

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