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Comment: Multi-factorial, longitudinal disease progression analysis with unbalanced patie by Dylan.Sheerin • 0
Thank you very much, Gordon. I'll give voomLmFit a go! And for comparisons between the cohorts I presume duplicateCorrelation with standar…
Answer: Multi-factorial, longitudinal disease progression analysis with unbalanced patie by Gordon Smyth 50k
Including subjectID in the design matrix always accounts for unbalanced sampling and patient variation but subjects with incomplete records…
Comment: Log-cpm values from limma by Gordon Smyth 50k
No, it does not mean that. `voom()` uses the design matrix, including the W covariates, to compute precision weights but not to adjust the …
Comment: Extremely small p-values using Limma for proteomic data by Abbey • 0
This is the code. The only part I changed was adding the contrasts.fit as you suggested. Thanks for taking a look! ``` # Load necessary …
Comment: Extremely small p-values using Limma for proteomic data by James W. MacDonald 65k
Probably. I would not expect such large fold changes. But without seeing your code, who knows?
Votes
Answer: Multi-factorial, longitudinal disease progression analysis with unbalanced patie
Answer: Extremely small p-values using Limma for proteomic data
Bioconductor 3.19 is Released!
A: Volcanoplot with limma - RAW P-values or Adj.P-Values
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