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Bioc2023
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News:
Reminder: BioC2023 in-person registration closes 19th July!
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11 weeks ago
Maria Doyle
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May 31st is the last day to nominate for Bioc2023 Awards!
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4 months ago
Maria Doyle
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Last Week to Nominate for Bioc2023 Awards!
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shepherl
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5 months ago • updated 4 months ago
shepherl
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Bioconductor Long-term Contribution Award
Bioc2023
Bioconductor
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shepherl
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5 months ago • updated 4 months ago
shepherl
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BioC2023 abstract submission is now open!
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written 7 months ago by
Maria Doyle
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Seeking members for BioC2023 organizing committee
BioC2023
Bioconductor
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8 months ago
Maria Doyle
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Bioc2023
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Bioconductor
10 months ago
shepherl
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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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