Package: preciseTAD
Type: Package
Title: preciseTAD: A machine learning framework for precise TAD
        boundary prediction
Version: 1.21.0
Authors@R: c(
    person("Spiro", "Stilianoudakis", 
        email = "stilianoudasc@vcu.edu", 
        role = c("aut")),
    person("Mikhail", "Dozmorov", 
        email = "mikhail.dozmorov@gmail.com", 
        role = c("aut", "cre")))
Description: preciseTAD provides functions to predict the location of
        boundaries of topologically associated domains (TADs) and
        chromatin loops at base-level resolution. As an input, it takes
        BED-formatted genomic coordinates of domain boundaries detected
        from low-resolution Hi-C data, and coordinates of
        high-resolution genomic annotations from ENCODE or other
        consortia. preciseTAD employs several feature engineering
        strategies and resampling techniques to address class
        imbalance, and trains an optimized random forest model for
        predicting low-resolution domain boundaries. Translated on a
        base-level, preciseTAD predicts the probability for each base
        to be a boundary. Density-based clustering and scalable
        partitioning techniques are used to detect precise boundary
        regions and summit points. Compared with low-resolution
        boundaries, preciseTAD boundaries are highly enriched for CTCF,
        RAD21, SMC3, and ZNF143 signal and more conserved across cell
        lines. The pre-trained model can accurately predict boundaries
        in another cell line using CTCF, RAD21, SMC3, and ZNF143
        annotation data for this cell line.
License: MIT + file LICENSE
Depends: R (>= 4.1)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat, BiocCheck, BiocManager, BiocStyle
VignetteBuilder: knitr
Imports: S4Vectors, IRanges, GenomicRanges, randomForest, ModelMetrics,
        e1071, PRROC, pROC, caret, utils, cluster, dbscan, doSNOW,
        foreach, pbapply, stats, parallel, gtools, rCGH
biocViews: Software, HiC, Sequencing, Clustering, Classification,
        FunctionalGenomics, FeatureExtraction
BugReports: https://github.com/dozmorovlab/preciseTAD/issues
URL: https://github.com/dozmorovlab/preciseTAD
Config/pak/sysreqs: make libbz2-dev libicu-dev liblzma-dev libpng-dev
        libxml2-dev libssl-dev xz-utils zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2025-10-29 15:02:20 UTC
RemoteUrl: https://github.com/bioc/preciseTAD
RemoteRef: HEAD
RemoteSha: 301ea2e424c54510dc5e9e8dc13e905417e81bfb
NeedsCompilation: no
Packaged: 2025-10-30 08:38:49 UTC; root
Author: Spiro Stilianoudakis [aut],
  Mikhail Dozmorov [aut, cre]
Maintainer: Mikhail Dozmorov <mikhail.dozmorov@gmail.com>
Built: R 4.6.0; ; 2025-10-30 08:42:30 UTC; windows
