3
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3
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Log-cpm values from limma
limma edgeR RNASeq
updated 4 hours ago by 50k • written 22 days ago by • 0
2
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9
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228
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Extremely small p-values using Limma for proteomic data
Proteomics limma
2 days ago • updated 10 hours ago Abbey • 0
2
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5
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149
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deseq2 results
DESeq2 DifferentialExpression rnaseqGene DifferentialRegulation
2 days ago • updated 5 hours ago sajadahmad41454 • 0
1
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0
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262
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News: Nominations for Bioconductor Awards 2024! Deadline May 15
Recognition Awards Bioconductor Bioc204
6 weeks ago • updated 20 hours ago shepherl 3.9k
1
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2
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Multi-factorial, longitudinal disease progression analysis with unbalanced patient sampling - duplicateCorrelation or blocking?
rna-seq duplicateCorrelation limma voom
1 day ago • updated 7 hours ago Dylan.Sheerin • 0
0
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1
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Differential gene expression analysis results
DESeq2 DifferentialExpression
updated 1 hour ago by ★ 4.1k • written 1 hour ago by • 0
0
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39
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How to use bootRanges to bootstrap small RNA loci (nullranges package)
bootRanges nullranges
15 months ago • updated 17 hours ago Poonam • 0
0
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DSS CpG coverage threshold
DSS WGBS coverage
updated 19 hours ago by • 0 • written 6.6 years ago by ▴ 30
0
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Recommendations on deploying cytoviewer shiny.appobj to shinyapps.io?
cytoviewer ShinyApps
11 hours ago neilzhao ▴ 30
9 results • Page 1 of 1
Recent ...
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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
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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