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Help! Gene Ontology Enrichment Analysis

Hi there, This is my first time doing GO enrichment and I am a little confused and could do with some help.

I'm doing a meta analysis of diff. tissues and now trying to do a GO analysis of the Fisher's findings.

I've found GoExpress and topGO as tools, but their instruction guides are a mystery to me. I am not sure what they want and they also ask for annotations, which is a little tricky in a meta analysis of different platforms?

For example, running the below gives me the error code "invalid genes selected".

DE_genes_CD <- subset(blood_sorted, Fishers.P.Value < 0.001)$Symbol
back_genes_idx <- genefinder(as.matrix(blood), as.character(DE_genes_CD),
                             method="manhattan", scale="none")

I'm sure I'm overlooking something or not approaching/understanding this the right way.

Any help/hints/code would be much appreciated!!!!

Many thanks!

ontology r goexpress topgo microarray
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updated by EagleEye EagleEye • written by ab123 • ab123

Please paste example data here (head or top 5 lines)

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written by cpad0112 cpad0112 
> all.genes <- sort(unique(as.character(blood_sorted$Symbol)))
> int.genes <- sample(x = all.genes, size = 1000)
> int.genes <- factor(as.integer(all.genes %in% int.genes))
> names(int.genes) = all.genes
> selGenes <- sample(ls(illuminaHumanv3GO))
> gene2GO <- lapply(mget(selGenes, envir = illuminaHumanv3GO), names)
> gene2GO[sapply(gene2GO, is.null)] <- NA
> go.obj <- new("topGOdata", ontology='BP'
+               , allGenes = int.genes
+               , annot = annFUN.gene2GO
+               , gene2GO = gene2GOID
+ )

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
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written by ab123 • ab123

Here is the crude example R script that worked. Try looking at the structure of your object/df.

=========

library(Biobase)
data("geneData")
data=tail(geneData)
data
genes=c("31734_at","31738_at")
str(genes)
genefinder(data,genes, numResults=2, scale="none",  method="euclidean")

Result

===========

> genefinder(data,genes, numResults=2, scale="none",  method="euclidean")
[[1]]
[[1]]$indices
[1] 6 2

[[1]]$dists
[1] 545.1294 576.7866


[[2]]
[[2]]$indices
[1] 6 3

[[2]]$dists
[1] 274.8154 544.4757

==========

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written by cpad0112 cpad0112

Hi there,

Does that work without the expression values?

You see, I'm working with already existing Fisher's P.values in a data.frame which I can easily change to a matrix, but I don't have expression values in there.

Thank you!

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written by ab123 • ab123

3 answers

You could use the OmicsBox Software (https://www.biobam.com/omicsbox/) to do Gene Ontology Enrichment Analysis. You can have a look at the user manual here for GSEA and the Fishers Exact Test here: http://manual.omicsbox.biobam.com/user-manual/module-functional-analysis/enrichment-analysis/

If you have the functional annotation (GO terms) for your species you just need a list of IDs you want to test for functional enrichment.

These OmicsBox video tutorials might help: GSEA: Fisher's Exact Test:

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written by sgoetz123 • sgoetz123

Have you tried blast2go?

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written by Mehmet Mehmet

No, but I was looking for a way to do this in R, not an outside software. Either way, thanks for suggesting!

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written by ab123 • ab123

If you have list of gene symbols, use this simple tool and has detailed instructions Gene Set Clustering based on Functional annotation (GeneSCF)

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written by EagleEye EagleEye

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