Bioconductor Affy

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2.1k

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Pathways probe affy Pathways probe affy

written 17.7 years ago by mike Ad. ▴ 30

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468

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GEO affy

5 weeks ago • updated 4 weeks ago Kurtis • 0

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2.2k

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Bioconductor Install affy

updated 5 months ago by ATpoint ★ 4.1k • written 17 months ago by laujihen • 0

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affy affy

updated 9 weeks ago by Gordon Smyth 50k • written 19.0 years ago by SAURIN ★ 1.1k

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2.0k

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Annotation affy oligo ffpe Annotation affy oligo ffpe

written 10.3 years ago by Guest User ★ 13k

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367

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frmaTools affy

updated 11 weeks ago by James W. MacDonald 65k • written 11 weeks ago by michelafrancesconi8 • 0

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233

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maplot_function rma_function ExpressionSet MicroarrayData affy

6 weeks ago Mj.A. • 0

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1.4k

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multtest affy multtest affy

updated 8 months ago by Amruta • 0 • written 20.7 years ago by Bob ▴ 20

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621

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crlmm hapmapsnp6 genomewidesnp6Crlmm affy

updated 10 months ago by Kevin Blighe ★ 3.9k • written 10 months ago by Vincent J. Carey, Jr. 6.7k

9 results • Page 1 of 1

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Answer: Differential gene expression analysis results by ATpoint ★ 4.1k

Pease do not open multiple posts for the same issue: https://support.bioconductor.org/p/9158194/#9158222 The support site is not meant f…

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…

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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

Bioconductor 3.19 is Released!

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