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limma Intercept vs No-intercept models completely changing DMR results?
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Timecourse RNASeq analysis
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Once again a "Model matrix not full rank"
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updated 11 hours ago by 65k • written 1 day ago by ▴ 130
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Why does GSEA on edgeR results for randomized samples give highly significant p-values?
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Too many significant genes when integrating gtex and tcga
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CombineArrays for EPIC and EPIC V2
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4 weeks ago • updated 4 hours ago Kim • 0
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package goseq seems to be not available on the latest version of R
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updated 1 hour ago by 50k • written 4 hours ago by • 0
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One error problem occurred caused by data type during using GDCprepare function of TCGAbiolinks to handle TCGAbiolinks BRCA data
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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. That is because goseq depends on txbmaker, which is itself not yet available for Bioc…
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…
Comment: CombineArrays for EPIC and EPIC V2 by Kim • 0
Thank you Tim, this is a great help in getting me started!
Comment: Too many significant genes when integrating gtex and tcga by Michael Love 41k
Yes, this was one of the aspects we highlighted in the 2014 paper, and it's also in the workflow. Check these places first. Also take a st…
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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
A: Print Differentially Expressed Exons From Dexseq Results
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