TFBlearner/DESCRIPTION at main · ETHZ-INS/TFBlearner · GitHub

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Package: TFBlearner
Title: Functionality for training TF-specific classifiers to predict TF bindings based on ATAC-seq data.
Version: 0.1.2
Authors@R:
    person("Emanuel", "Sonder", , "emanuel.sonder@hest.ethz.ch", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-4788-9508"))
Description: Functionality for training TF-specific classifiers to predict TF bindings based on ATAC-seq data. Classifiers are trained using ChIP-seq peaks as ground truth for TF binding. Functions for compiling features, training and predicting are provided. For convenience all features and datasets used are contained within a MultiAssayExperiment object.
License: GPL-3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Depends:
    Matrix,
    MultiAssayExperiment,
    lightgbm,
    data.table,
    HDF5Array,
    R (>= 3.5)
Imports:
        BiocParallel,
        Biostrings,
        chromVAR,
        DelayedMatrixStats,
        DiceKriging,
        GenomicAlignments,
        GenomeInfoDb,
        GenomicRanges,
        GenomicScores,
        Hmisc,
        IRanges,
        MatrixGenerics,
        mlr3,
        mlr3misc,
        mlr3tuning,
        mlr3learners,
        mlr3mbo,
        mlr3measures,
        MotifDb,
        motifmatchr,
        paradox,
        pdist,
        R6,
        ranger,
        RcppML,
        rgenoud,
        Rsamtools,
        rhdf5,
        sparseMatrixStats,
        S4Vectors,
        preprocessCore,
        PRROC,
        SummarizedExperiment,
        TFBSTools,
        universalmotif
Suggests:
    testthat (>= 3.0.0),
    covr,
    BSgenome.Hsapiens.UCSC.hg38,
    phastCons100way.UCSC.hg38
Config/testthat/edition: 3
LazyData: true