[Bioc-devel] Too many dependencies / MultiAssayExperiment + rtracklayer

Shraddha Pai @hr@ddh@@p@| @end|ng |rom utoronto@c@
Tue Sep 21 15:53:19 CEST 2021


Hi Zugang,
Thanks for the tip on pkgndep - very helpful visualization. If I understand
correctly, rows in the matrix are sorted by number of dependency packages
loaded by a package required by netDx. Can see the long stripes for the
packages you mention.
Those packages are used by 1-2 minor functions for visualizing results so I
could indeed move them to Suggests.

Question: When moving packages from Depends to SUGGESTS, I should also
remove the @imports tag from inline Roxygen2 documentation? And then in the
function itself, should I qualify the functions used by package name?
e.g. if I remove RCy3 from the Depends section, I would remove @imports
RCy3 from the function doc of the corresponding function. Then within that
function wherever I use a function I would prepend with RCy3:: (e.g.
RCy3::commandsGET() instead of commandsGET()).

Is this correct?

Thanks,Shraddha

On Mon, Sep 20, 2021 at 3:41 PM 顾祖光 <jokergoo using gmail.com> wrote:

> An analysis with the pkgndep package (https://github.com/jokergoo/pkgndep)
> shows
> the three heaviest packages are RCy3, clusterExperiment and netSmooth. If
> you can
> move these three packages to SUGGESTS (where the packages are loaded only
> when related
> functions are called), I think the number of dependent packages will be
> reduced
> to 130~150, or maybe less.
>
> library(pkgndep)
> x = pkgndep("netDx")
> plot(x)
>
> The plot is here
> https://github.com/jokergoo/ComplexHeatmap/files/7198274/test.pdf
>
> Cheers,
> Zuguang
>
>
> On Mon, 20 Sept 2021 at 20:37, Shraddha Pai <shraddha.pai using utoronto.ca>
> wrote:
>
>> Hello again,
>> I'm trying to simplify the dependencies for my package "netDx", make it
>> easier to install. It's currently got over 200(!) + some Unix libraries
>> that need to be installed.
>>
>> 1. I ran pkgDepMetrics() from BiocPkgTools to find less-needed pkgs, and
>> the package with the most dependencies is MultiAssayExperiment (see below
>> email). I'm using MAE to construct a container - is there a way to use
>> @importFrom calls to reduce MAE dependencies?
>>
>> 2. Another problem package is rtracklayer which requires Rhtslib, which
>> requires some unix libraries: zlib1g-dev libbz2-dev liblzma-dev. I'm not
>> sure which functionality in the package requires rtracklayer - how can I
>> tell? Is there a way to simplify / reduce these deps so the user doesn't
>> have to install all these unix packages?
>>
>> 3. Are there other "problem packages" you can see that I can remove? Let's
>> assume for now ggplot2 stays because people find it useful to have
>> plotting
>> functions readily available.
>>
>> Thanks very much in advance,
>> Shraddha
>> ---
>> "ImportedAndUsed" "Exported" "Usage" "DepOverlap" "DepGainIfExcluded"
>> "igraph" 1 782 0.13 0.05 0
>> "ggplot2" 1 520 0.19 0.19 0
>> "pracma" 1 448 0.22 0.03 0
>> "plotrix" 1 160 0.62 0.03 1
>> "S4Vectors" 2 283 0.71 0.03 0
>> "grDevices" 1 112 0.89 0.01 0
>> "httr" 1 91 1.1 0.05 0
>> "scater" 1 85 1.18 0.4 0
>> "utils" 3 217 1.38 0.01 0
>> "GenomeInfoDb" 1 60 1.67 0.06 0
>> "stats" 12 449 2.67 0.01 0
>> "bigmemory" 1 35 2.86 0.03 3
>> "RCy3" 12 386 3.11 0.32 18
>> "BiocFileCache" 1 29 3.45 0.23 3
>> "glmnet" 1 24 4.17 0.07 2
>> "parallel" 2 33 6.06 0.01 0
>> "combinat" 1 13 7.69 0.01 1
>> "MultiAssayExperiment" 4 46 8.7 0.22 1
>> "foreach" 2 23 8.7 0.02 0
>> "graphics" 8 87 9.2 0.01 0
>> "GenomicRanges" 15 106 14.15 0.08 0
>> "rappdirs" 1 7 14.29 0.01 0
>> "reshape2" 1 6 16.67 0.05 0
>> "RColorBrewer" 1 4 25 0.01 0
>> "netSmooth" 1 3 33.33 0.82 3
>> "Rtsne" 1 3 33.33 0.02 0
>> "doParallel" 1 2 50 0.03 0
>> "ROCR" 2 3 66.67 0.05 4
>> "clusterExperiment" NA 122 NA 0.74 0
>> "IRanges" NA 255 NA 0.04 0
>>
>>
>> --
>>
>> *Shraddha Pai, PhD*
>> Principal Investigator, OICR
>> Assistant Professor, Department of Molecular Biophysics, University of
>> Toronto
>> shraddhapai.com; @spaiglass on Twitter
>> https://pailab.oicr.on.ca
>>
>>
>> *Ontario Institute for Cancer Research*
>> MaRS Centre, 661 University Avenue, Suite 510, Toronto, Ontario, Canada
>> M5G
>> 0A3
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>>
>>
>>
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