Problem with universe argument in enrichKEGG
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ruiqi.li ▴ 10
@5d6dd1ca
Last seen 20 months ago
United States

Hi all!

I am trying to do KEGG enrichment with enrichKEGG, I was wondering if I need to specify universe argument. Could you please help me with it?

  1. In the documentation, it says "universe: background genes. If missing, the all genes listed in the database (eg TERM2GENE table) will be used as background." However, enrichKEGG doesn't take TERM2GENE argument. If the universe is not specified, what will be used as the universe?

It returns unused argument (TERM2GENE = Transcriptome) If I specify TERM2GENE.

  1. Should I use the KEGG column from the "KEGG Orthology to Genes mapping" as the universe?

enr_results <- enrichKEGG(DEG$KEGG, organism='ko', universe = Transcriptome$KEGG, pvalueCutoff = 0.05, pAdjustMethod = "BH", qvalueCutoff = 0.05, minGSSize = 5)

Here are what my files look like:

  1. KEGG to DEG mappings

    > head(DEG)
     KEGG Gene
    1 K17277  FS_gene_3
    2 K14700 FS_gene_11
    3 K14701 FS_gene_11
    
  2. KEGG to whole transcriptome mappings

    head(Transcriptome)
     KEGG Gene
    1 K02727  FS_gene_1
    2 K17277  FS_gene_3
    3 K17307 FS_gene_10
    

Thanks a lot!

KEGG clusterProfiler keggorthology • 2.7k views
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enrichKEGG automatically uses all genes present in the KEGG gene sets as universe.

See also my post here: clusterProfiler for KEGG enrichment (non-model species) Over-Representation Analysis (for an illustration of this), and the answer of Erqiang Hu below.

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Basti ▴ 780
@7d45153c
Last seen 3 days ago
France

This very insightful paper was released last year on the good practice to conduct when running GO : https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009935

According to this paper, "In the case of ORA for differential expression (eg: RNA-seq), a whole genome background is inappropriate because in any tissue, most genes are not expressed and therefore have no chance of being classified as DEGs. A good rule of thumb is to use a background gene list consisting of genes detected in the assay at a level where they have a chance of being classified as DEG [5–7]. Using the whole genome background gene list may be suitable in cases where all genes have the capacity of being detected, for example in studies of genetic variation (eg: [8]). However the problem becomes more acute when the proportion of measured genes/proteins is small, for example in proteomics and single-cell RNA-sequencing where only a few thousand analytes are detected."

Then I think you should select all the genes expressed in your experiment as the background gene list.

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Thanks a lot! This is so helpful!

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A follow up question: My experiment involves multiple treatments and multiple tissues. I have across tissue comparisons and within tissue comparsions. When I am doing within tissue comparsion, should I only use genes found expressed in that tissue as the background gene list? or would it be more proper to use all the genes that I am testing as a background gene list for all comparisons?

Thanks a lot!

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If you do within tissue comparison, I would only use the genes found expressed in that tissue indeed because if you take all the genes, some may not be relevant because they are never expressed in this specific tissue

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Erqiang Hu ▴ 50
@13766876214-21289
Last seen 10 months ago
Guangzhou

There is no need to specify universe argument. When you use enrichKEGG to do enrichment analysis, itwill automatically use all genes that can be annotated to the pathways as the background.

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Would that be a problem for non-model organism? I understand that you can specify organsim if you are studying organisms on KEGG organism list. I will need to specify ko as my organism. Would that universe too broad? Would you suggest using enricher and provide my own universe instead?

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