PICB

[frahrend]

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• Repository: https://github.com/HaaseLab/PICB

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[bioc-issue-bot]

Hi @frahrend

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: PICB
Title: piRNA Cluster Builder
Version: 0.99.0
Authors@R: c(person("Pavol", "Genzor",  role = c("aut")),
    person("Aleksandr", "Friman", email="[email protected]",  role = c("aut")),
    person("Daniel", "Stoyko", role = c("aut")),
    person("Parthena", "Konstantinidou", email="[email protected]", role = c("aut")),
    person("Franziska", "Ahrend", email="[email protected]",  role = c("aut", "cre"), comment=c(ORCID = "0009-0004-7464-3444")),
    person("Zuzana", "Loubalova", email="[email protected]",  role = c("aut")), 
    person("Yuejun", "Wang", email="[email protected]",  role = c("aut")),
    person("Hernan", "Lorenzi", email="[email protected]",  role = c("aut")),
    person("Astrid D", "Haase", email="[email protected]",  role = c("aut")))
Description: piRNAs (short for PIWI-interacting RNAs) and their PIWI protein partners play a key role in fertility 
    and maintaining genome integrity by restricting mobile genetic elements (transposons) in germ cells. 
    piRNAs originate from genomic regions known as piRNA clusters. The piRNA Cluster Builder (PICB) is 
    a versatile toolkit designed to identify genomic regions with a high density of piRNAs. It constructs 
    piRNA clusters through a stepwise integration of unique and multimapping piRNAs and offers wide-ranging 
    parameter settings, supported by an optimization function that allows users to test different parameter 
    combinations to tailor the analysis to their specific piRNA system. The output includes extensive metadata 
    columns, enabling researchers to rank clusters and extract cluster characteristics. 
License: CC0
Encoding: UTF-8
Imports:
    utils,
    GenomicRanges,
    GenomicAlignments,
    GenomeInfoDb,
    Biostrings,
    Rsamtools,
    data.table,
    IRanges,
    seqinr,
    stats,
    openxlsx,
    dplyr, 
    S4Vectors
Suggests: 
    knitr,
    rtracklayer, 
    testthat,
    BiocStyle,
    prettydoc,
    BSgenome,
    BSgenome.Dmelanogaster.UCSC.dm6,
    rmarkdown,
    ggplot2
VignetteBuilder: knitr
BugReports: https://github.com/HaaseLab/PICB/issues
URL: https://github.com/HaaseLab/PICB
biocViews: Genetics, GenomeAnnotation, Sequencing, FunctionalPrediction, Coverage, Transcriptomics
RoxygenNote: 7.3.2

[lshep]

The current vignette is not appropriate for Bioconductor. All your code sections are eval=FALSE. Code must be evaluated.

[frahrend]

Dear @lshep
Thank you for your feedback! Previously, half of the code was evaluated, with the initial sections simply serving as an introduction to the package and its functions.
We have now combined these parts into a unified vignette, where the vast majority of code is directly executable. The only exceptions are (1) installation of dependencies and the package itself (as suggested) and (2) an optional method for loading the reference genome via a FASTA file. Preferred methods, such as using a BSgenome or providing a Seqinfo object, remain fully executable.
Thank you again for your feedback! An updated version is now available in our repo.