Issues w/expected input genes

[jinkinson]

I have been having trouble with two DOSE functions: gseNCG and enrichDGN. In both cases when I try to use either function on my list of sorted geneIDs and corresponding p-values I get an error message containing a line telling me what the "expected input gene ID" is. BTW, the geneIDs in my dataset are from Mus musculus, so given that using gseNCG on the default geneList produces an output listing the organism as "homo sapiens", I think maybe the problem might be that the functions I was using were automatically using homo sapiens, in which case I'd need to somehow change it to use mus musculus instead. Below____ is the entire error message generated from me running enrichDGN:

--> No gene can be mapped.... --> Expected input gene ID: 653509,79644,3054,1855,10561,7050 --> return NULL... NULL

And the corresponding error message from gseNCG: preparing geneSet collections... --> Expected input gene ID: 999,677,2065,55294,2625,2033 Error in check_gene_id(geneList, geneSets) : --> No gene can be mapped....

[huerqiang]

The NCG and DisGeNET databases are used for human disease analysis.

[jinkinson]

@huerqiang Thanks so much for the quick and informative response!

[sagay2022]

@huerqiang I am having a similar issue, however, I am using mouse data and mouse genome annotation (org.Mm.eg.db). I input code and receive

preparing geneSet collections... --> Expected input gene ID: ENSMUSG00000027424,ENSMUSG00000021541,ENSMUSG00000030968,ENSMUSG00000003731,ENSMUSG00000052144,ENSMUSG00000024639 Error in check_gene_id(geneList, geneSets) : --> No gene can be mapped....

`library(clusterProfiler) library(pathview) library(enrichplot) library(ggplot2) library(DOSE) library(AnnotationDbi) library(org.Mm.eg.db) library(stats4) library(parallel) library(Biobase) library(IRanges) library(S4Vectors)

#read in the res file from DESeq analysis df <- read.csv(file.choose(), header=TRUE) #get the log2 fold change original_gene_list <- df$log2FoldChange #naming the vector names(original_gene_list) <- df$X #omit the NA values from the data gene_list <- na.omit(original_gene_list) #sorting the list in decreasing order of log2 Fold Change gene_list = sort(gene_list, decreasing = TRUE)

#prepare data for input to make figures gse <- gseGO(geneList=gene_list, ont ="ALL", keyType = "ENSEMBL", nPerm = 10000, minGSSize = 3, maxGSSize = 800, pvalueCutoff = 0.05, verbose = TRUE, pAdjustMethod = "BH", OrgDb = "org.Mm.eg.db", )

require(DOSE) dotplot(gse, showCategory=10, split=".sign") + facet_grid(.~.sign)`

Do I need to use another annotation instead of this?