SpatialFeatures

[shazanfar]

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• Repository: https://github.com/SydneyBioX/SpatialFeatures

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[bioc-issue-bot]

Hi @shazanfar

Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.

The DESCRIPTION file for this package is:

Package: SpatialFeatures
Title: Entropy-based subcellular and supercellular features for molecule-resolved spatial omics datasets
Version: 0.99.0
Authors@R: c(
    person("Shila", "Ghazanfar", email = "shazanfar@gmail.com",
    role = c("aut", "cre", "ctb"),comment = c(ORCID = "0000-0001-7861-6997")),
    person("Guan", "Gui", role = "ctb")
    )
Description: This package uses molecule-level information to extract new 
  cell-level features as an alternative to simply calculating gene counts. By 
  using four categories, sub-sector, super-sector, super-sector and 
  super-concentric segmentations of cells, SpatialFeatures then uses entropy 
  as a metric to arrive at a cell-by-gene level feature. Overall, this means 
  that we can extract more nuanced information from molecule-resolved spatial
  gene expression for further downstream analysis with SingleCellExperiment.
License: GPL-2
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Depends: R (>= 4.4.0),
    MoleculeExperiment,
    SingleCellExperiment,
    dplyr,
    purrr,
    parallel
Imports:
    terra,
    rlang
Suggests:
    knitr,
    ggplot2,
    BiocStyle
VignetteBuilder: knitr
biocViews: Spatial, GeneExpression
URL: https://sydneybiox.github.io/SpatialFeatures/
BugReports: https://github.com/sydneybiox/SpatialFeatures/issues

[bioc-issue-bot]

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[bioc-issue-bot]

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on the Bioconductor Single Package Builder.

On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details.

The following are build products from R CMD build on the Single Package Builder: Linux (Ubuntu 24.04.1 LTS): SpatialFeatures_0.99.0.tar.gz

Links above active for 21 days.

Remember: if you submitted your package after July 7th, 2020, when making changes to your repository push to git@git.bioconductor.org:packages/SpatialFeatures to trigger a new build. A quick tutorial for setting up remotes and pushing to upstream can be found here.

[bioc-issue-bot]

Received a valid push on git.bioconductor.org; starting a build for commit id: ca193f7b5d125718d31ff84faf65652111e6c9d9

[bioc-issue-bot]

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on the Bioconductor Single Package Builder.

Congratulations! The package built without errors or warnings on all platforms.

Please see the build report for more details.

The following are build products from R CMD build on the Single Package Builder: Linux (Ubuntu 24.04.1 LTS): SpatialFeatures_0.99.1.tar.gz

Links above active for 21 days.

Remember: if you submitted your package after July 7th, 2020, when making changes to your repository push to git@git.bioconductor.org:packages/SpatialFeatures to trigger a new build. A quick tutorial for setting up remotes and pushing to upstream can be found here.

[bioc-issue-bot]

A reviewer has been assigned to your package for an indepth review. Please respond accordingly to any further comments from the reviewer.

[HelenaLC]

misc

• [ ] Please consider implementing unit tests; we strongly encourage them.
• [ ] In the README, please include installation instructions using BiocManager::install().
• [ ] In the DESCRIPTION, consider adding biocViews suggested in the build report.

docs

• [ ] Please add providence and source information on example_me.
• [ ] Consider adding a package .man/help page (?SpatialFeatures).
• [ ] Consider hyperlinking external packages using BiocStyle::Biocpkg(".") (or similar for packages hosted on CRAN or GitHub).
• [ ] Love the plots! But a little more methodological detail would be highly appreciated, in both R docs and the vignette (e.g., how is entropy computed? what values can it take? how are those interpreted?).
• [ ] Similarly, spatialFeatures() lists the segmentations its using, but these are not explained (and are not obvious to interpret, to me at least...); consider briefly explaining these in both in R doc and the vignette.

code

• [ ] Avoid sapply() and use vapply() instead.
• [ ] I see many functions expecting an me with 0 checks on class/validity of that input; please add something of that sort as to avoid weird failure downstream.
• [ ] Related to the above, consider adding minimal validity checks on input arguments (e.g., input is a scalar logical, a list of data.frames etc.).
• [ ] Somewhere, argument featureTypes is passed to match.arg() with a set of valid options provided in the function definition, but EntropyMatrix is missing this.