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Dylan.Sheerin
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Abbey
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Kim
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123
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253
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1.2k
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221
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20 days ago • updated 17 days ago
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Gordon Smyth
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hortense96
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426
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175
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avery
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4 weeks ago
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7 weeks ago • updated 6 weeks ago
Efra
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9 weeks ago • updated 6 weeks ago
Lily Cheang
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9 weeks ago
dl17032000
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10 weeks ago
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updated 10 weeks ago by
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updated 10 weeks ago by
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11 weeks ago
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11 weeks ago • updated 10 weeks ago
alessandro
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updated 12 weeks ago by
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written 12 weeks ago by
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3 months ago • updated 10 weeks ago
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updated 12 weeks ago by
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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
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Gordon Smyth
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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
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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…
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