Bioconductor Rflowcyt

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flow cytometry flowcore flowclean rflowcyt flowworkspace

updated 8.4 years ago by Jiang, Mike ★ 1.3k • written 8.5 years ago by magomudw • 0

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prada rflowcyt prada rflowcyt

updated 18.0 years ago by Nolwenn LeMeur ▴ 140 • written 18.0 years ago by dr. Treszl András ▴ 10

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Survival Infrastructure Cancer hexbin prada rfcdmin rflowcyt Survival Infrastructure

updated 18.0 years ago by Seth Falcon ★ 7.4k • written 18.0 years ago by Ulrik Stervbo ▴ 80

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prada rflowcyt prada rflowcyt

18.0 years ago Nolwenn LeMeur ▴ 140

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Biobase rflowcyt Biobase rflowcyt

updated 18.0 years ago by Nolwenn LeMeur ▴ 140 • written 18.0 years ago by Ulrik Stervbo ▴ 80

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17.9 years ago Ulrik Stervbo ▴ 80

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Genetics Cancer rflowcyt Genetics Cancer rflowcyt

17.7 years ago Ryan Brinkman ▴ 10

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rflowcyt rflowcyt

updated 16.8 years ago by Byron Ellis ▴ 100 • written 16.8 years ago by M. Jankowski ▴ 160

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rflowcyt rflowcyt

18.0 years ago Nolwenn LeMeur ▴ 140

9 results • Page 1 of 1

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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…

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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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