islify

[jtheorell]

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• Repository: https://github.com/jtheorell/islify

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[bioc-issue-bot]

Hi @jtheorell

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: islify
Title: Automatic scoring and classification of cell-based assay images
Version: 0.99.1
Date: 2025-01-10
biocViews: Software,CellBasedAssays,BiomedicalInformatics,FeatureExtraction,
    Visualization,Pathways,Classification
Authors@R: 
    person('Jakob', 'Theorell', email = "[email protected]",
        role = c("aut", "cre"), comment=c(ORCID="0000-0001-8752-3151"))
Description: This software is meant to be used for classification of images of
    cell-based assays for neuronal surface autoantibody detection or similar
    techniques. It takes imaging files as input and creates a composite score
    from these, that for example can be used to classify samples as negative or
    positive for a certain antibody-specificity. The reason for its name is
    that I during its creation have thought about the individual picture as an
    archielago where we with different filters control the water level as well
    as ground characteristica, thereby finding islands of interest. 
License: GPL-3
URL: https://github.com/Bioconductor/islify
BugReports: https://github.com/Bioconductor/islify/issues
Encoding: UTF-8
RoxygenNote: 7.3.2
Depends: R (>= 4.3)
Imports:
    autothresholdr (>= 1.4.2), Matrix (>= 1.6.1), RBioFormats (>= 1.0.0), 
    tiff (>= 0.1.12), png (>= 0.1.8), dbscan (>= 1.1.12), abind (>= 1.4.8), 
    methods (>= 4.3.3), stats (>= 4.3.3)
Suggests: knitr, rmarkdown, testthat, BiocStyle
VignetteBuilder: knitr

[vjcitn]

Thanks for this submission. Please improve the introduction in the vignette. The DESCRIPTION file actually has more background information than the intro to the vignette. Please help a naive visitor to the vignette to understand what kinds of studies your package addresses. References to the literature to give context in the intro are greatly appreciated.

[jtheorell]

Dear Vince,
Thank you very much for observing this glaring omission. I hope it makes more sense now in version 0.99.2!
By the way: I am aware of the fact that the package does not address a genetic question per se, but I interpreted the more general text including other techniques, such as imaging, as also including solutions for this kind of data. I really hope that is correct, as I believe that there is a researcher community much in need of this package that would benefit greatly from having it quality controlled through BioConductor. No idea of that is of relevance, but we will publish a paper soon where this software will play a significant role, where we analyse approximately 10 000 images with it, so it is reasonably "big data".
All the best
Jakob