Hello,

I am trying to install IlluminaHumanMethylation450k.db but can't manage to do so:

Error : .onLoad failed in loadNamespace() for 'IlluminaHumanMethylation450k.db', details:
  call: NULL
  error: 'fun' is defunct.
Use 'FDb.InfiniumMethylation.hg19' instead.
Use 'FDb.InfiniumMethylation.hg18' instead.
Use 'mapToGenome() function in minfi or methylumi' instead.
See help("Defunct")
Error: loading failed
Execution halted
ERROR: loading failed

I know the package is deprecated. What I wanted to use is the function to map 450K probes to ensembl gene ids (GRCh37) which had been previously done using that package in our study, and for consisteny reasons I would need the same mapping again.

I could not find a way to get this mapping with mapToGenome() or FDb.InfiniumMethylation.hg19, but if there is a way I am not aware of, please tell me.
Otherwise, if anybody knows what to do to get IlluminaHumanMethylation450k.db working again, I would be very happy. I've tried for many hours since yesterday without success. Solutions like in ‘IlluminaHumanMethylation450k.db’ had non-zero exit status did also not help, as here the error is a different one, but I can't find out how to solve it.

Best,
Simone

> sessionInfo()
R version 3.2.2 (2015-08-14)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Gentoo/Linux

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8   
 [6] LC_MESSAGES=C              LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
[1] tools_3.2.2

I 'solved' it by commenting the code calling .Defunct

#    if(interactive()){
#        .Defunct(new=c(paste0('FDb.InfiniumMethylation.hg', c(19, 18)),
#                   'mapToGenome() function in minfi or methylumi'))
#    }

Simone

If you are trying to reproduce old results you should use the older version of R/Bioconductor that you used before.

(This is really the only good reason for using outdated versions of R/Bicoonductor.)