Error when I load my own data using ViSEAGO create_topGO

问题

I have trouble creating topGO object using my own data. Wondering if someone can help me with this!

I'm following a couple of tutorials and steps mentioned in the original ViSEAGO paper. Here are chunks from the tutorial and their links.

From the publication: ViSEAGO offers all statistical tests and algorithms developed in the Bioconductor topGO R package, taking into account the topology of GO graph by using ViSEAGO::create_topGO- data method followed by the topGO::runTestmethod.

Under 'Functional GO enrichment' in the tutorial, the following piece of code is used to generate the topGO object.

# create topGOdata for BP
BP<-ViSEAGO::create_topGOdata(
    geneSel=selection,
    allGenes=background,
    gene2GO=myGENE2GO, 
    ont="BP",
    nodeSize=5
)

I also referred to topGO's tutorial to make sure my data types are correct. Yet, there are some errors, that I have trouble dealing with.

For my data, I have the following code.

> ##################
> # create topGOdata for BP
> BP<-ViSEAGO::create_topGOdata(
+   geneSel=geneList_g1,
+   allGenes=topDiffGenes(geneList_g1),
+   gene2GO=myGENE2GO, 
+   ont="BP",
+   nodeSize=5
+ )

#error message:
allGenes contain genes redondancy.
duplicate elements were removed.
Error in .local(.Object, ...) : allGenes must be a factor with 2 levels

In my case, geneList_g1 is a named num with gene symbols and p-values (length 23 differentially expressed genes as shown below). The organism being studies is Mus musculus.

> dput(geneList_g1)
c(Klf4 = 0.596, Pdk2 = 0.278, Pink1 = 0.192, Hsp90ab1 = 0.142, 
Cdkn1a = 0.132, App = 0.0197, Lep = 0.0165, Igf1 = 0.00138, Bcl6 = 0.001, 
Pfkm = 0.000264, Rbp4 = 0.000175, Pck1 = 0.000162, Adipoq = 9.13e-05, 
B2m = 1.63e-05, Pde4d = 1.8e-06, Ppargc1a = 1.04e-07, Igfbp4 = 1.01e-07, 
Apod = 5.52e-08, Foxo1 = 7.05e-12, Ide = 1.29e-12, Nr1d1 = 7.68e-17, 
Apoe = 1.48e-25, Pdk4 = 4.5e-57)

Using another command to creat topGO object, I get the following error.

> mysampleGOdata <- new("topGOdata",
+                     description = "my Simple session",
+                     ontology = "BP",
+                     allGenes = geneList_g1,
+                     geneSel = topDiffGenes,
+                     nodeSize = 1,
+                     annot = annFUN.db,
+                     affyLib = affyLib)

Building most specific GOs .....
    ( 0 GO terms found. )

Build GO DAG topology ..........
    ( 0 GO terms and 0 relations. )
Error in if (is.na(index) || index < 0 || index > length(nd)) stop("vertex is not in graph: ",  : 
  missing value where TRUE/FALSE needed

Any help is much appreciated!! Thanks in advance! :)

回答1:

You need to provide the correction annotation and in your case, a vector of TRUE / FALSE. So to start:

geneList_g1 = c(Klf4 = 0.596, Pdk2 = 0.278, Pink1 = 0.192, Hsp90ab1 = 0.142, 
Cdkn1a = 0.132, App = 0.0197, Lep = 0.0165, Igf1 = 0.00138, Bcl6 = 0.001, 
Pfkm = 0.000264, Rbp4 = 0.000175, Pck1 = 0.000162, Adipoq = 9.13e-05, 
B2m = 1.63e-05, Pde4d = 1.8e-06, Ppargc1a = 1.04e-07, Igfbp4 = 1.01e-07, 
Apod = 5.52e-08, Foxo1 = 7.05e-12, Ide = 1.29e-12, Nr1d1 = 7.68e-17, 
Apoe = 1.48e-25, Pdk4 = 4.5e-57)

Load libraries, org.Mm.eg.db is the mouse annotation:

library(org.Mm.eg.db)
library(topGO)

And we do:

UNI=keys(org.Mm.eg.db, keytype ='SYMBOL')
geneList <- factor(as.integer(UNI %in% names(geneList_g1)))
names(geneList) = UNI

If you have a background of other genes, you basically use UNI as your list of genes tested, and follow up with geneList:

mysampleGOdata <- new("topGOdata",
                     description = "my Simple session",
                     ontology = "BP",
                     allGenes = geneList,
                     nodeSize = 1,
                     annot = annFUN.org,
                     mapping="org.Mm.eg.db", 
                     ID = "SYMBOL")

resultFisher <- runTest(mysampleGOdata, algorithm = "classic", statistic = "fisher")

 head(GenTable(mysampleGOdata,fisher=resultFisher),1)
       GO.ID                      Term Annotated Significant
1 GO:0006006 glucose metabolic process       194          12
  Expected  fisher
1     0.19 1.0e-19

来源：https://stackoverflow.com/questions/59639543/error-when-i-load-my-own-data-using-viseago-create-topgo

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rna-seq