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limma Differentialenrichmentanalysis DEP

updated 8 weeks ago by Gordon Smyth 50k • written 9 weeks ago by Laura • 0

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LFQ DEPpackage run_app('LFQ') ShinyApps DEP

updated 9 months ago by Ram ▴ 200 • written 10 months ago by d.kozhevnikova ▴ 10

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DEP

updated 16 days ago by shepherl 3.9k • written 16 days ago by Namrata • 0

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Proteomics DEP limma

written 2.8 years ago by barrypraveen • 0

4 results • Page 1 of 1

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Answer: How to use bootRanges to bootstrap small RNA loci (nullranges package) by Poonam • 0

Hi Michael, I think there is something wrong with the generation of nullranges. I was working with small RNA and methylation overlaps. …

Answer: Once again a "Model matrix not full rank" by swbarnes2 ★ 1.3k

Replicate numbers, like the 1 in control_1 are fine in sample names, but never add them to anything else in colData. From the computer's p…

Answer: limma Intercept vs No-intercept models completely changing DMR results? by Gordon Smyth 50k

I'll add a little bit of general advice to James' answer. You seem to have the misunderstanding that you can change the design matrix but …

Answer: package goseq seems to be not available on the latest version of R by Gordon Smyth 50k

It is true that goseq isn't available for Bioc 3.19 (as at 4 May 2024). In the meantime, you could consider using the goana() and kegga() …

Answer: limma Intercept vs No-intercept models completely changing DMR results? by James W. MacDonald 65k

This part: ``` design_intercept <- model.matrix(~Alt+Sex+Age+PC1, data=targets_Sherpa) colnames(design_intercept) <- c("AltSHP_LA","Al…

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Answer: Why does GSEA on edgeR results for randomized samples give highly significant p-

Answer: limma Intercept vs No-intercept models completely changing DMR results?

Answer: CombineArrays for EPIC and EPIC V2

Answer: Too many significant genes when integrating gtex and tcga

Comment: Too many significant genes when integrating gtex and tcga

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