Hi, I am using clusterProfiler to do an enrichment analysis. However, I get the warning ' No gene can be mapped.... --> Expected input gene ID: ND6,ND4,COX3,ND1,ND5,ATP6 --> return NULL...'. I am studying a non-model organism, the 'Vulpes lagopus'. My script is as follows,

mycounts<-read.csv("-B5_Counts-Arctic-fat.csv",row.names = 1)

head(mycounts)
dim(mycounts)
library(dplyr)
library(DESeq2)
mycounts <- mycounts %>%mutate_if(is.factor, ~as.numeric(as.character(.)))
mymeta<-read.csv("-B5_mymeta.csv",stringsAsFactors = T)
mycountsGroups <- mymeta$Group
colData <- data.frame(row.names=colnames(mycounts),
                      group_list=mycountsGroups)
dds <- DESeqDataSetFromMatrix(countData = mycounts,
                              colData = colData,
                              design = ~group_list,
                              tidy = F)
keep <- rowSums(counts(dds)>10) >4
dds.keep <- dds[keep, ]
dim(dds.keep)
degobj <- DESeq(dds.keep);degobj
countdds <- counts(degobj, normalized = T) 
deg.res1 <- results(degobj, contrast=c("group_list","HFB","LFB"), lfcThreshold = 0,
                    pAdjustMethod = 'fdr')
dim(deg.res1)
apply(deg.res1,2, function(x) sum(is.na(x)))
deg.res1$padj[is.na(deg.res1$padj)] <- 1
table(is.na(deg.res1$padj))
summary(deg.res1) 
library(dplyr)
res_1<-data.frame(deg.res1)
res_1 %>%
  mutate(group = case_when(log2FoldChange >0.5 & padj <= 0.05 ~ "UP",log2FoldChange <-0.5 & padj <= 0.05 ~ "DOWN",TRUE ~ "NOT_CHANGE")) -> res_2
table(res_2$group)
upsig <- res_2[grep(pattern = "UP",res_2[,7]),]
downsig <- res_2[grep(pattern = "DOWN",res_2[,7]),]
deg <- rbind(upsig,downsig)
# non-model, but have the genome
BiocManager::install("AnnotationHub")
BiocManager::install("biomaRt")
# load package
library(AnnotationHub)
library(biomaRt)
# make a orgDb
hub <- AnnotationHub::AnnotationHub()
# 
query(hub, "Vulpes lagopus")
Vulpes.OrgDb <- hub[["AH96456"]]
columns(Vulpes.OrgDb)
head(keys(Vulpes.OrgDb,keytype = "ACCNUM"))
head(keys(Vulpes.OrgDb,keytype = "GOALL"))
library(clusterProfiler)
df2 <- bitr(row.names(upsig), fromType = "SYMBOL",
            toType = c("ENTREZID"),
            OrgDb = Vulpes.OrgDb) 
genelist <- df2$ENTREZID
enrich.go.BP = enrichGO(gene       =genelist,
                        OrgDb = Vulpes.OrgDb,
                        keyType      = 'ENTREZID',ont= "CC",
                        pvalueCutoff = 0.05,
                        pAdjustMethod = "BH",
                        qvalueCutoff = 0.05,
                        )

However, I always got the warning as mentioned above.

Looking forward to some help! Thank you!

While the output to your query to enrichGO has 'bp' in the name, you are actually querying on 'CC'. And that's a pretty sparse thing to query on. Also, you are using an old version of R/Bioc, so you should upgrade

> library(AnnotationHub)
.> hub <- AnnotationHub()
snapshotDate(): 2022-04-25
> Vulpes.OrgDb <- hub[["AH96456"]]
Error: AH96456 is an OrgDb resource.
  orgDb resources are generated for specific biocversions.
  Requested resource works with biocversion: 3.14
  To find a resource appropriate for your biocversion try the following query:
      query(ah,'org.Vulpes_lagopus.eg.sqlite')

> Vulpes.OrgDb <- hub[["AH101318"]]
downloading 1 resources
retrieving 1 resource
  |======================================================================| 100%

loading from cache

## Now for some inside baseball...
## we first get a connection to the underlying SQLite DB

> library(DBI)
> con <- dbconn(Vulpes.OrgDb)

## Now do a query to get all the GO CC terms (and ancestors) for each gene

> z <- dbGetQuery(con, "select GID, GO from go_cc_all inner join genes using('_id');")
> head(z)
       GID         GO
1 23629747 GO:0016021
2 23629747 GO:0005743
3 23629747 GO:0070469
4 23629747 GO:0005575
5 23629747 GO:0016020
6 23629747 GO:0031224

## How large is this data.frame?
> dim(z)
[1] 283   2

## Ooof. How many unique Gene IDs?
> length(unique(z[,1]))
[1] 13

## double Ooof.
> unique(z[,1])
 [1] "23629747" "23629748" "23629749" "23629750" "23629751" "23629752"
 [7] "23629753" "23629754" "23629755" "23629756" "23629757" "23629758"
[13] "23629759"

## what about BP?
> z <- dbGetQuery(con, "select GID, GO from go_bp_all inner join genes using('_id');")
> dim(z)
[1] 197   2
> length(unique(z[,1]))
[1] 9

Long story short, the annotation package has vanishingly small numbers of genes that are annotated to any GO terms, so you are not going to be able to get reasonable results. You might be able to use blast2go to get a better mapping, but IIRC, that costs money unless there's a free trial period. And I don't use clusterProfiler, so I have no idea if you can feed in a data.frame of ID -> GO mappings. But you could use kegga from the limma package if you had such a thing.