Bioconductor Rnaseq

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171

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DESeq2 StatisticalMethod Proteomics DifferentialExpression RNASeq

updated 8 days ago by ATpoint ★ 4.1k • written 8 days ago by james.zhang20 • 0

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157

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DESeq2 RNAseq

updated 15 days ago by Michael Love 42k • written 15 days ago by kcarey • 0

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174

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limma RNASeq voom

written 17 days ago by taur.vil • 0

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221

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technicalReplicates BatchEffect limma RNASeq

20 days ago • updated 18 days ago catv • 0

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115

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DESeq2 LongRead DEXSeq IsoformSwitchAnalyzeR RNASeq

updated 21 days ago by Michael Love 42k • written 22 days ago by 09191919 • 0

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256

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limma edgeR RNASeq

updated 8 hours ago by Gordon Smyth 50k • written 22 days ago by Shaimaa Gamal • 0

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872

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clusterProfiler RNASeq

updated 16 days ago by Guangchuang Yu ★ 1.2k • written 14 months ago by ruiqi.li ▴ 10

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930

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SingleCell RNASeq RNASeqData scRNAseq

updated 22 days ago by wichaidi • 0 • written 17 months ago by irvin.ng • 0

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1.8k

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sgseq rnaseq

updated 4 days ago by Sara • 0 • written 6.7 years ago by Sylvain Foisy ▴ 80

9 results • Page 1 of 1

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Comment: Extremely small p-values using Limma for proteomic data by James W. MacDonald 65k

If you ever find yourself using the `@` function, you should reconsider what you are doing. There are vanishingly small instances when an e…

Comment: How to use bootRanges to bootstrap small RNA loci (nullranges package) by Michael Love 42k

Here is some example code <https://gist.github.com/mikelove/cbbc84634b6854c865cb5eb08ad9b245>

Comment: How to use spike-in information (sequences from another species) with DESeq2::DE by maria.soler • 0

Hi, I have a question barely related to this topic. Do you use a custom reference genome combining your organism and the one used as a spik…

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.

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Comment: Log-cpm values from limma

Comment: deseq2 results

Answer: Multi-factorial, longitudinal disease progression analysis with unbalanced patie

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