Bioconductor Confounders

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scRNA-seq MAST confounders

updated 5.2 years ago by Andrew_McDavid ▴ 270 • written 5.2 years ago by ramonmassoni ▴ 10

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2.0k

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limma limma-voom limma design matrix confounders

updated 6.7 years ago by Aaron Lun ★ 28k • written 6.7 years ago by S.Bamopoulos ▴ 10

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1.3k

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deseq2 confounders nanostring rnaseq differential gene expression

updated 6.9 years ago by Michael Love 43k • written 6.9 years ago by kim.malek88 • 0

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2.5k

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ruvseq deseq2 model.matrix confounders

updated 7.6 years ago by davide risso ▴ 980 • written 7.6 years ago by heikki.sarin ▴ 10

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2.9k

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deseq2 confounders design matrix rnaseq

7.9 years ago • updated 7.8 years ago lina.faller ▴ 10

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2.2k

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minfi bumphunter confounders

updated 7.9 years ago by James W. MacDonald 68k • written 7.9 years ago by gft219 • 0

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2.1k

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edgeR paired samples confounders model.matrix

updated 8.7 years ago by Ryan C. Thompson ★ 7.9k • written 8.7 years ago by manasishah86 ▴ 30

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5.0k

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deseq2 rnaseq_analysis variancestabilizingtransformation confounders

updated 8.8 years ago by Michael Love 43k • written 8.8 years ago by ompandey ▴ 10

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5.2k

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Deseq2 dds confounders

updated 9.2 years ago by Michael Love 43k • written 9.2 years ago by colaneri ▴ 30

9 results • Page 1 of 1

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Comment: how many significant figures are there in DESeq2 output by ATpoint ★ 4.7k

If you want consistency then use a fixed software environment like Docker, wirh fixed code and thresholds that make sense. Rounding to near…

Comment: Compare TCGA-PAAD with GTEx gene expression by Jane • 0

why aren't there any answers?

Comment: Too many significant genes when integrating gtex and tcga by Jane • 0

I encountered the same issue: too many DEGs after limma analysis. It is sad that until today we can still see the paper published where GTE…

Comment: how many significant figures are there in DESeq2 output by Matthew McCormack ▴ 180

Thank you for your reply. It is good to know that cutoff of 0.05 means less than 0.05. My concerns are about consistency and reproducibili…

Comment: DiffBind edgeR normalization --- why are the normalization factors all equal to by ATpoint ★ 4.7k

No, normalization factors from edgeR rather than size factors from DESeq2 are not proportional, it's a different concept and implementation…

Votes

A: Unbalanced experiment with multiple samples from each patient.

Unbalanced experiment with multiple samples from each patient.

Answer: Vertical line at A=0, nothing else, on MA plot

Answer: GSVA Error Code "Calling gsva(expr=., gset.idx.list=., method=., ...) is defunct

Answer: Group-specific condition effects with individuals nested: matrix is not full ra

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