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Design
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Once again a "Model matrix not full rank"
DESeq2
design
coldata
updated 6 days ago by
swbarnes2
★ 1.4k • written 7 days ago by
arfranco
▴ 130
2
votes
3
replies
298
views
edgeR, 3 x 2 design with a batch effect and contrasts
design
edgeR
contrasts
updated 7 weeks ago by
Gordon Smyth
50k • written 7 weeks ago by
JKim
• 0
2
votes
2
replies
270
views
Question about extracting co-efficients for pairwise comparisons in edgeR
limma
fit
design
RNASeq
edgeR
8 weeks ago
Sabiha
▴ 20
2
votes
2
replies
294
views
Limma design for 3 replicated time courses comparing treatment vs placebo
design
limma
3 months ago
SamGG
▴ 350
3
votes
6
replies
848
views
Question on constructing design matrix and defining contrasts for analysis
wgcna
DESeq2
edgeR
limma
design
updated 11 months ago by
Gordon Smyth
50k • written 11 months ago by
mohammedtoufiq91
▴ 10
5 results • Page
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Comment: deseq2 results
by
sajadahmad41454
• 0
thank you for your response, should i remove or discard that sample? since the red outlier on left represents one of healthy samples.
Comment: deseq2 results
by
swbarnes2
★ 1.4k
It looks like the PCA plot of a real RNASeq experiment. The red outlier on the left might be the mathematical reason why you have few vali…
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!
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 with the W covariates, to compute precision weights but not to adjust the log-cp…
Votes
Comment: deseq2 results
Comment: deseq2 results
Answer: Multi-factorial, longitudinal disease progression analysis with unbalanced patie
Answer: Extremely small p-values using Limma for proteomic data
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