Bioconductor SpliceR

Showing : SpliceR • reset

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1.6k

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splicer

updated 7.0 years ago by k.vitting.seerup ▴ 120 • written 7.0 years ago by aditi ▴ 20

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2.0k

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splicer cummerbund

updated 7.5 years ago by lmanchon • 0 • written 8.5 years ago by weisbeal ▴ 10

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2.3k

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SpliceR Cuffdiff

updated 9.3 years ago by deppt002 • 0 • written 9.5 years ago by mfahim • 0

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1.8k

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rtracklayer Granges spliceR

updated 9.4 years ago by Michael Lawrence ★ 11k • written 9.4 years ago by mfahim • 0

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1.1k

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splicer rnaseq

updated 9.6 years ago by k.vitting.seerup ▴ 120 • written 10.2 years ago by hliang ▴ 20

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1.6k

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Annotation spliceR Annotation spliceR

updated 9.6 years ago by k.vitting.seerup ▴ 120 • written 10.3 years ago by hliang ▴ 20

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1.3k

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spliceR

updated 9.6 years ago by k.vitting.seerup ▴ 120 • written 9.7 years ago by knight2ni • 0

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1.9k

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bitseq spliceR

9.6 years ago elle ▴ 10

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1.6k

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dexseq bitseq spliceR

9.7 years ago elle ▴ 10

9 results • Page 1 of 1

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Answer: Limma - using both array and spot weights in lmFit by henty1308 • 0

[BitLife][1] characters can go to jail for crimes. Escape or reform to return to normal life. [1]: https://bitlife-game.io

Answer: Limma - using both array and spot weights in lmFit by Gordon Smyth 52k

Was answered here: https://support.bioconductor.org/p/17028/

Comment: Easiest way to convert read10xMolInfo data into a dataframe in R with gene label by daldabrown9 • 0

For more info visit us on [R350 status check][1] [1]: https://sassagrantstatuscheck.co.za/

Answer: Margins for gene_set_enrichment_plot by Leonardo Collado Torres ★ 1.1k

Hi, In version 1.19.4 of `spatialLIBD` @lahuuki re-implemented the `gene_set_enrichment_plot()` function using `ComplexHeatmap::Heatmap(…

Comment: miRTarRnaseq library by mercedeh.movassagh ▴ 20

Maria please read the mirTarRnaSeq paper. In particular, Supplemental Table 2, clarifies all the statistical models, inputs and outputs. If…

Votes

Answer: Fold change calculation in Diffbind vs. DESEQ2?

Fold change calculation in Diffbind vs. DESEQ2?

FeatureCounts Output Counts at Exon Level Using Default Settings, want gene level

Answer: FeatureCounts Output Counts at Exon Level Using Default Settings, want gene leve

Whether to build DESeq2 model with all data and then contrast groups or subset groups first, build model and then contrast?

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