[Rd] [BioC] enabling reproducible research & R package management & install.package.version & BiocLite

Paul Gilbert pgilbert902 at gmail.com
Tue Mar 5 23:34:09 CET 2013

(More on the original question further below.)

On 13-03-05 09:48 AM, Cook, Malcolm wrote:
> All,
> What got me started on this line of inquiry was my attempt at
> balancing the advantages of performing a periodic (daily or weekly)
> update to the 'release' version of locally installed R/Bioconductor
> packages on our institute-wide installation of R with the
> disadvantages of potentially changing the result of an analyst's
> workflow in mid-project.

I have implemented a strategy to try to address this as follows:

1/ Install a new version of R when it is released, and packages in the R 
version's site-library with package versions as available at the time 
the R version is installed. Only upgrade these package versions in the 
case they are severely broken.

2/ Install the same packages in site-library-fresh and upgrade these 
package versions on a regular basis (e.g. daily).

3/ When a new version of R is released, freeze but do not remove the old 
R version, at least not for a fairly long time, and freeze 
site-library-fresh for the old version. Begin with the new version as in 
1/ and 2/. The old version remains available, so "reverting" is trivial.

The analysts are then responsible for choosing the R version they use, 
and the library they use. This means they do not have to change R and 
package version mid-project, but they can if they wish. I think the 
above two libraries will cover most cases, but it is possible that a few 
projects will need their own special library with a combination of 
package versions. In this case the user could create their own library, 
or you might prefer some more official mechanism.

The idea of the above strategy is to provide the stability one might 
want for an ongoing project, and the possibility of an upgraded package 
if necessary, but not encourage analysts to remain indefinitely with old 
versions (by say, putting new packages in an old R version library).

This strategy has been implemented in a set of make files in the project 
RoboAdmin available at http://automater.r-forge.r-project.org/. It can 
be done entirely automatically with a cron job. Constructive comments 
are always appreciated.

(IT departments sometimes think that there should be only one version of 
everything available, which they test and approve. So the initial 
reaction to this approach could be negative. I think they have not 
really thought about the advantages. They usually cannot test/approve an 
upgrade without user input, and timing is often extremely complicate 
because of ongoing user needs. This strategy is simply shifting 
responsibility and timing to the users, or user departments, that can 
actually do the testing and approving.)

Regarding NFS mounts, it is relatively robust. There can be occasional 
problems, especially for users that have a habit of keeping an R session 
open for days at a time and using site-library-fresh packages. In my 
experience this did not happen often enough to worry about a "blackout 

Regarding the original question, I would like to think it could be 
possible to keep enough information to reproduce the exact environment, 
but I think for potentially sensitive numerical problems that is 
optimistic. As others have pointed out, results can depend not only on R 
and package versions, configuration, OS versions, and library and 
compiler versions, but also on the underlying hardware. You might have 
some hope using something like an Amazon core instance. (BTW, this 
problem is not specific to R.)

It is true that restricting to a fixed computing environment at your 
institution may ease things somewhat, but if you occasionally upgrade 
hardware or the OS then you will probably lose reproducibility.

An alternative that I recommend is that you produce a set of tests that 
confirm the results of any important project. These can be conveniently 
put in the tests/ directory of an R package, which is then maintained 
local, not on CRAN, and built/tested whenever a new R and packages are 
installed. (Tools for this are also available at the above indicated web 
site.) This approach means that you continue to reproduce the old 
results, or if not, discover differences/problems in the old or new 
version of R and/or packages that may be important to you. I have been 
successfully using a variant of this since about 1993, using R and 
package tests/ since they became available.


> I just got the "green light" to institute such periodic updates that
> I have been arguing is in our collective best interest.  In return,
> I promised my best effort to provide a means for preserving or
> reverting to a working R library configuration.
> Please note that the reproducibility I am most eager to provide is
> limited to reproducibility within the computing environment of our
> institute, which perhaps takes away some of the dragon's nests,
> though certainly not all.
> There are technical issues of updating package installations on an
> NFS mount that might have files/libraries open on it from running R
> sessions.  I am interested in learning of approaches for
> minimizing/eliminating exposure to these issue as well.  The
> first/best approach seems to be to institute a 'black out' period
> when users should expect the installed library to change.   Perhaps
> there are improvements to this????
> Best,
> Malcolm
> .-----Original Message----- .From: Mike Marchywka
> [mailto:marchywka at hotmail.com] .Sent: Tuesday, March 05, 2013 5:24
> AM .To: amackey at virginia.edu; Cook, Malcolm .Cc:
> r-devel at r-project.org; bioconductor at r-project.org;
> r-discussion at listserv.stowers.org .Subject: RE: [Rd] [BioC] enabling
> reproducible research & R package management &
> install.package.version & BiocLite . . .I hate to ask what go this
> thread started but it sounds like someone was counting on .exact
> numeric reproducibility or was there a bug in a specific release? In
> actual .fact, the best way to determine reproducibility is run the
> code in a variety of .packages. Alternatively, you can do everything
> in java and not assume .that calculations commute or associate as the
> code is modified but it seems .pointless. Sensitivity determination
> would seem to lead to more reprodicible results .than trying to keep
> a specific set of code quirks. . .I also seem to recall that FPU may
> have random lower order bits in some cases, .same code/data give
> different results. Alsways assume FP is stochastic and plan .on
> anlayzing the "noise." . . .----------------------------------------
> .> From: amackey at virginia.edu .> Date: Mon, 4 Mar 2013 16:28:48
> -0500 .> To: MEC at stowers.org .> CC: r-devel at r-project.org;
> bioconductor at r-project.org; r-discussion at listserv.stowers.org .>
> Subject: Re: [Rd] [BioC] enabling reproducible research & R package
> management & install.package.version & BiocLite .> .> On Mon, Mar 4,
> 2013 at 4:13 PM, Cook, Malcolm <MEC at stowers.org> wrote: .> .> > *
> where do the dragons lurk .> > .> .> webs of interconnected
> dynamically loaded libraries, identical versions of .> R compiled
> with different BLAS/LAPACK options, etc. Go with the VM if you .>
> really, truly, want this level of exact reproducibility. .> .> An
> alternative (and arguably more useful) strategy would be to cache .>
> results of each computational step, and report when results differ
> upon .> re-execution with identical inputs; if you cache sessionInfo
> along with .> each result, you can identify which package(s) changed,
> and begin to hunt .> down why the change occurred (possibly for the
> better); couple this with .> the concept of keeping both code *and*
> results in version control, then you .> can move forward with a
> (re)analysis without being crippled by out-of-date .> software. .> .>
> -Aaron .> .> -- .> Aaron J. Mackey, PhD .> Assistant Professor .>
> Center for Public Health Genomics .> University of Virginia .>
> amackey at virginia.edu .> http://www.cphg.virginia.edu/mackey .> .>
> [[alternative HTML version deleted]] .> .>
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