Bioconductor GeneSet

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geneset GeneSetEnrichment msigdb

12 months ago Seongsu • 0

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1.8k

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gseGO GeneSet clusterProfiler GeneSetEnrichment

updated 21 months ago by James W. MacDonald 68k • written 21 months ago by manuelsokolov • 0

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singscore GSVA GSEA subtypes geneset

updated 4.3 years ago by Dharmesh D Bhuva • 0 • written 6.1 years ago by Pietro ▴ 40

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GSVA geneset RNASeq TCGA subtypes

6.3 years ago Pietro ▴ 40

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kegg geneset genelist gage package

updated 7.7 years ago by Gordon Smyth 52k • written 7.7 years ago by sup230 ▴ 30

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gseabase geneset

updated 8.3 years ago by Martin Morgan 25k • written 8.3 years ago by siajunren • 0

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cummerbund readcufflinks geneset

9.3 years ago alessio.stevano • 0

7 results • Page 1 of 1

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Comment: CluserProfiler message "No gene can be mapped" by Carolina • 0

There is, the overlap that reads out is ( Genes in common: 368 of 368 ). Here is the link for [background genes][1], [term2gene][2], [term2…

Comment: Differing results with DESeq2 by JKim • 0

My two cents. I think it would be more straightforward if you use cellmeans model. Have a look at [A guide to creating design matrices for …

Answer: CluserProfiler message "No gene can be mapped" by James W. MacDonald 68k

Your gene IDs are things like this: `Mpyr-NLJ1B.v3.hap1.scaffold1.g290550`, and the genes in your term2gene table are things like this: `Mp…

Answer: RNA-seq input to GRaNIE by James W. MacDonald 68k

This is [covered in the vignette.][1] [1]: https://bioconductor.org/packages/release/bioc/vignettes/GRaNIE/inst/doc/GRaNIE_packageDe…

Answer: Help using reduceSimMatrix with a custom annotation by sergisayolspuig ▴ 80

Hi there, `reduceSimMatrix()` expects a "GOALL" keytype in the OrgDb object when called with `children=TRUE` (which is the default for thi…

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remove X and Y chromosome genes in RNA-seq data using DESeq2 pipeline

How to remove X & Y chromosome genes from RNAseq data

Is it advisable to remove X and Y chromosome genes in mouse bulk RNA-seq data at the level of the count matrix?

A: Unbalanced experiment with multiple samples from each patient.

A: Understanding contrasts limma

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