I'm the maintainer for the package 'rase' (link) .
I haven't changed the code at all since Nov 9, 2015, when the package could load without problems. However, I have received emails asking about the following problem when loading the package:
> library(rase)
Error in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]) :
there is no package called ‘Biostrings’
Error: package or namespace load failed for ‘rase’
I tried then to do it in my own computer, and I received the same message. Between the last time I loaded the package successfully (Nov 2015) and now, I upgraded R to v 3.2.3. Naively, I reinstalled v3.2.2, but the same error appears. I have checked rase code (git here) thoroughly, but no changes have been made and there is no reference whatsoever to 'Biostrings' (or any function within). 'rase' dependencies and imports do not include 'Biostrings'.
Any help would be much appreciated as I don't know why this is happening (I'm a novice when creating packages). I guess I could install 'Biostrings', but I don't want to make a seemingly unnecessary dependency.
Here is my sessionInfo:
> sessionInfo()
R version 3.2.2 (2015-08-14)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.11.2 (El Capitan)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ape_3.4 data.table_1.9.6
loaded via a namespace (and not attached):
[1] quadprog_1.5-5 lattice_0.20-33 mvtnorm_1.0-3 msm_1.6
[5] MASS_7.3-43 chron_2.3-47 grid_3.2.2 nnls_1.4
[9] nlme_3.1-121 magrittr_1.5 Matrix_1.2-2 splines_3.2.2
[13] tools_3.2.2 igraph_1.0.1 maps_3.0.2 parallel_3.2.2
[17] numDeriv_2014.2-1 survival_2.38-3 mnormt_1.5-3 clusterGeneration_1.3.4
[21] animation_2.4 expm_0.999-0
Biostrings is a BioConductor package which you install following the instructions on this page :
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("Biostrings")
If you add BioC as a known repository on your system, it will be installable via install.packages()
too. Eg this would do
r <- getOption("repos")
r["CRAN"] <- "http://cran.rstudio.com"
r["BioCsoft"] <- "http://www.bioconductor.org/packages/release/bioc"
options(repos = r)
in your .Rprofile
or Rprofile.site
.
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