Bioconductor GenomicDataCommons

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TCGA GenomicDataCommons GDC

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TCGA GenomicDataCommons

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GenomicDataCommons R

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GenomicDataCommons

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TCGA GenomicDataCommons

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TCGAutils TCGAbiolinks GenomicDataCommons

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genomicdatacommons tcga gdc rest http

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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?

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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

Answer: Mac ARM64 build report for BioC 3.19 from 'kjohnson3' reporting ERROR which it

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