Broader testing - Please test the installation of my stan R package - does it succeed?


#1

Hello,

I started with some testing from people of my lab, but…

I would like to have a better feeling whether my Stan R package encounters problem for third party installation. Would you like to try it and report any error?

image

ARMET-tc infers rates of changes in tissue composition across covariates of interest (e.g., treatment status, time or disease grade)

# Installation
library(devtools)  
install_github("stemangiola/ARMET", args = "--preclean", build_vignettes = FALSE, auth_token = "37c5c6238136a6804d336d9a7078eece993ce870", password="x-oauth-basic")  
library(ARMET) 

# Inference
results = 
  ARMET_tc(
    mix =          test_data$mix, 
    my_design =    test_data$design_matrix, 
    cov_to_test =  test_data$cov_to_test, 
    do_debug = F
   )
   
# Report
ARMET_getFit(results)
ARMET_plotFit(results, "immune_cell")

Thanks!


#2

It looks like ‘preprocessCore’, and the ‘edgeR’ packages are required, but not available in CRAN.


#3

Thanks Aaron,

True they are part of the Bioconductor repository. Now I will have a look to include packages from another repository other than CRAN.

Thanks!


#4

I found this suggestion

There is a trick for this: add biocViews: to the package’s DESCRIPTION and R will know to search the bioconductor repository automatically for package requirements. This trick is not documented anywhere.

here

However I am still trying to understand how to add biocViews: (when, after what, including what) with pretty sparse documentation…


#5

I know nothing about biocViews, but here’s an example:

Is there really no R documentation on this anywhere? (I suppose I shouldn’t be so suprised.)