Bioconductor Annotationhubdata

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2.0k

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clusterProfiler AnnotationHubData GO

updated 16 months ago by Guido Hooiveld ★ 3.7k • written 16 months ago by Lucía ▴ 10

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1.8k

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AnnotationHubData AnnotationForge

17 months ago Saber_J ▴ 10

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707

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AnnotationHubData PhyloProfile

16 months ago S.t ▴ 10

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629

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GenomicFeatures AnnotationHubData tximeta

updated 12 months ago by Michael Love 40k • written 12 months ago by Pratik Mehta ▴ 10

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491

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AnnotationHubData

updated 2.8 years ago by Kevin Blighe 3.8k • written 2.8 years ago by Bogdan ▴ 660

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174

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exon AnnotationHubData

4 months ago mahima.g • 0

6 results • Page 1 of 1

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Comment: Suggested package missing from Development version of Bioconductor by shepherl 3.5k

Have you tried reaching out to the maintainers? If they do not fix the package it will remain unavailable and cause ERROR in your package.…

Answer: Batch effect adjust in model matrix by ATpoint ★ 3.4k

Each sample is a different day, that is called "nested", so there is nothing you can do here. Next time do a better experimental design, he…

Comment: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts? by Michael Love 40k

Oh, I see. If you can't use counts + offset then I prefer lengthScaledTPM to DESeq2, i.e. `txi$counts` to `DESeqDataSetFromMatrix()`. So …

Comment: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts? by Christian • 0

I´m sorry causing confusion here, but the gene matrices I refer to are actually obtained via https://nf-co.re/rnaseq. The problem with the…

Comment: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts? by Michael Love 40k

For the reasons outlined in the Soneson paper, I'd prefer this pipeline: https://nf-co.re/rnaseq You cannot use these scaled TPM approach…

Votes

Comment: Batch correction and repeated measures

batch effect : comBat or blocking in limma ?

Batch correction and repeated measures

Comment: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts?

Comment: Phenotype effect - building a contrast matrix - grouping vs interaction

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