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/libblas.so.3
LAPACK: /usr/lib/libopenblasp-r0.2.19.so

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=en_US.UTF-8    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] 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

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

source("https://bioconductor.org/biocLite.R")
biocLite(pkgs_Im_intereseted_in)

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.