Hi,

I'm trying to run enrichment analysis on flybase gene ids using goana and kegga from limma. However I keep getting the same error 

fit <- glmFit(x, design)

lrt <- glmLRT(fit,coef=2)

kegga.de=kegga(lrt,species='Dm')

Error in kegga.default(de = DEGenes, universe = universe, ...) : 

No annotated genes found in universe

I've also tried using it with my own list of de flybase gene IDs and defining my own universe using a vector of flybase IDs but the same error occurs.

"org.Dm.eg.db" is installed.

Help would be much appreciated. Thanks in advance.

My sessionInfo below 

> sessionInfo()

R version 3.4.1 (2017-06-30)

Platform: x86_64-pc-linux-gnu (64-bit)

Running under: CentOS release 6.9 (Final)

Matrix products: default

BLAS: /opt/Modules/R/3.4.1/lib64/R/lib/libRblas.so

LAPACK: /opt/Modules/R/3.4.1/lib64/R/lib/libRlapack.so

locale:

 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C              

 [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    

 [5] LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   

 [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                 

 [9] LC_ADDRESS=C               LC_TELEPHONE=C            

[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

attached base packages:

[1] parallel  stats4    stats     graphics  grDevices utils     datasets 

[8] methods   base     

other attached packages:

[1] org.Dm.eg.db_3.5.0   GO.db_3.5.0          AnnotationDbi_1.40.0

[4] IRanges_2.12.0       S4Vectors_0.16.0     Biobase_2.36.2      

[7] BiocGenerics_0.24.0  edgeR_3.12.1         limma_3.26.9        

loaded via a namespace (and not attached):

 [1] locfit_1.5-9.1  Rcpp_0.12.13    lattice_0.20-35 digest_0.6.12  

 [5] grid_3.4.1      DBI_0.7         RSQLite_2.0     rlang_0.1.2    

 [9] blob_1.1.0      splines_3.4.1   bit64_0.9-7     bit_1.1-12     

[13] compiler_3.4.1  pkgconfig_2.0.1 memoise_1.1.0   tibble_1.3.4   

By default, kegga() will look in rownames(lrt) for the gene Ids.

KEGG supports either FlyBase CG Ids or Entrez Gene Ids (see below), so you have to supply one or the other. It doesn't support FlyBase FBgn Ids.

> g <- getGeneKEGGLinks("dme")
> head(g)
        GeneID     PathwayID
1 Dmel_CG10160 path:dme00010
2 Dmel_CG10202 path:dme00010
3 Dmel_CG10467 path:dme00010
4 Dmel_CG10924 path:dme00010
5 Dmel_CG10996 path:dme00010
6 Dmel_CG11140 path:dme00010
> g <- getGeneKEGGLinks("dme",convert=TRUE)
> head(g)
  GeneID     PathwayID
1  45880 path:dme00010
2  36649 path:dme00010
3  38697 path:dme00010
4  37130 path:dme00010
5  32345 path:dme00010
6  45398 path:dme00010

Note that org.Dm.eg.dg is not relevant here as it isn't used in a KEGGA analysis