GenomicRanges fails to load due to missing ngap method
Entering edit mode
Last seen 3.9 years ago

The Error

Hi, the GenomicRanges package (or namespace) v1.26.2 fails to load apparantly due to a missing ngap method for export.

> packageVersion("GenomicRanges")
[1] ‘1.26.2’
> library("GenomicRanges")
Error: package or namespace load failed for ‘GenomicRanges’ in loadNamespace(package, lib.loc):
 in ‘GenomicRanges’ methods for export not found: ngap
In addition: Warning message:
no function found corresponding to methods exports from ‘GenomicRanges’ for: ‘ngap’

I installed GenomicRanges and other R packages, when possible, from the Debian stretch distribution. But the error still occurred when I updated my Bioconductor packages and built them from source (by choosing a in Update all/some/none? [a/s/n]: that was prompted automatically following a call to biocLite).

Session Info

> sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 9 (stretch)

Matrix products: default
BLAS: /usr/lib/openblas-base/
LAPACK: /usr/lib/

 [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=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C            

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] GenomeInfoDb_1.10.3 IRanges_2.12.0      S4Vectors_0.16.0    BiocGenerics_0.24.0 knitr_1.17          setwidth_1.0-4     
[7] colorout_1.0-2     

loaded via a namespace (and not attached):
[1] compiler_3.4.1 XVector_0.14.0 tools_3.4.1    RCurl_1.95-4.8 bitops_1.0-6
software error genomicranges loadnamespace • 899 views
Entering edit mode
Last seen 3 months ago
United States

Usually this is a problem when mixing packages from different Bioconductor versions. Does BiocInstaller::biocValid() indicate packages that are too old / too new? If so, standardize on a single Bioconductor version.  Be sure to update packages in a new R session, and pay attention to any warnings / errors that occur during the process. I personally would following the Bioconductor recommendations and install packages with


installing any system dependencies with apt get; if you use apt get (or conda, or...), then I think you should stick to only using packages that can be installed via that mechanism.


Login before adding your answer.

Traffic: 305 users visited in the last hour
Help About
Access RSS

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6