Indeed. The wrong set of repos was used for the count:
db <- available.packages(repos=BiocManager::repositories(version="3.13"))
deps <- tools::package_dependencies("netDx", db, recursive=TRUE,
reverse=FALSE, which="strong")
lengths(deps)
# netDx
# 200
Fixed now: https://bioconductor.org/packages/3.14/netDx
Sorry for the inconvenience.
Cheers,
H.
On 18/10/2021 13:31, Marcel Ramos wrote:
Hi Shraddha,
Note that the badge on the landing page is using this formula (~ from
the `biocViews` package):
```r
db <- available.packages(repos = BiocManager::repositories())
deps <- tools::package_dependencies("netDx", db, recursive = TRUE,
reverse = FALSE, which = "strong")
lengths(deps)
#' netDx
#' 109
```
This number is not matching up with the value listed in the badge. Hervé
is currently looking into it
and will have an update soon.
Best regards,
Marcel
On 10/18/21 12:05 PM, Shraddha Pai wrote:
Hi all,
Despite moving rarely-used packages to Suggests and eliminating some (e.g.
TCGAutils), the number of dependencies is still listed as 200 for our
package netDx.
https://www.bioconductor.org/packages/devel/bioc/html/netDx.html#since
Is there anything else we can do to cut down on dependencies?
Thank you,
Shraddha
On Tue, Sep 21, 2021 at 5:35 PM Shraddha Pai<shraddha....@utoronto.ca>
wrote:
Hi Michael,
Thanks! Looks like the package trying to load 'rtracklayer' was
'TCGAutils' (see graph from Zugang above, generated using pkgndep - looks
to be quite useful). Turns out TCGAutils really wasn't necessary for my
package so I just took it out and removed all associated dependencies -
mercifully an easier fix.
Thanks for your help,
Shraddha
On Mon, Sep 20, 2021 at 2:57 PM Michael Lawrence <
lawrence.mich...@gene.com> wrote:
Hi Shraddha,
From the rtracklayer perspective, it sounds like Rsamtools is
(indirectly) bringing in those system libraries. I would have expected
zlibbioc to cover the zlib dependency, and perhaps bz2 and lzma
support is optional. Perhaps a core member could comment on that.
In the past, I've used this package
https://github.com/Bioconductor/codetoolsBioC to identify missing
NAMESPACE imports. In theory, you could remove the rtracklayer import
and run functions in that package to identify the symbol-level
dependencies. The output is a bit noisy though.
Btw, using @importFrom only allows you to be selective of symbol-level
dependencies, not package-level.
Michael
On Mon, Sep 20, 2021 at 11:37 AM Shraddha Pai<shraddha....@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
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