Package: ViralEntropR
Title: A Computational Pipeline for Entropy-Informed Detection of
        Emerging Viral Variants
Version: 0.6.2
Authors@R: c(
              person("Vadim", "Tyuryaev", ,"vadim.tyuryaev@gmail.com", 
                      role = c("aut", "cre"), 
                      comment = c(ORCID = "0009-0008-1361-6265")),
              person("Jane", "Heffernan", , "jmheffer@yorku.ca", 
                      role = c("aut")),
              person("Hanna", "Jankowski", , "hkj@yorku.ca", 
                      role = c("aut"))
             )
Description: Implements an entropy-informed pipeline for detecting
    emerging variants in viral amino acid sequence data, extending
    prior clustering-based approaches including hemagglutinin
    clustering methods (Li et al., 2015)
    <doi:10.1142/9789814667944_0018>. Provides a fully vectorized
    FASTA preprocessing toolkit covering header parsing, two-pass
    date and country extraction, ambiguous-residue filtering, and
    integer encoding under a 25-symbol amino acid alphabet. Computes
    per-site Shannon entropy across user-defined cumulative,
    sliding, or disjoint temporal partitions and clusters per-site
    entropy values using Gaussian mixture models via 'mclust'
    (Scrucca et al., 2016) <doi:10.32614/RJ-2016-021>. Quantifies
    temporal distributional shifts between partitions using the
    Hellinger distance (van der Vaart, 1998)
    <doi:10.1017/CBO9780511802256>, and detects temporal change
    points non-parametrically using energy statistics (Matteson and
    James, 2014) <doi:10.1080/01621459.2013.849605> via 'ecp' or
    wild binary segmentation (Fryzlewicz, 2014)
    <doi:10.1214/14-AOS1245> via 'HDcpDetect'. Per-site amino-acid 
    frequency tables and entropy trajectory plots characterize sequence 
    composition and evolutionary dynamics across time. A configurable 
    multi-variant simulation engine generates synthetic sequence 
    time series with known ground truth for benchmarking detection pipelines. 
    A curated dataset of SARS-CoV-2 Variants of Concern and Variants of
    Interest with associated lineage and surveillance metadata is
    included, along with a bundled National Center for Biotechnology
    Information (NCBI) Spike protein sample and vignettes
    demonstrating the full workflow.
License: MIT + file LICENSE
Language: en-GB
Date: 2026-05-07
URL: https://github.com/vadimtyuryaev/ViralEntropR,
        https://doi.org/10.5281/zenodo.19040165,
        https://vadimtyuryaev.github.io/ViralEntropR/
BugReports: https://github.com/vadimtyuryaev/ViralEntropR/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Imports: ggplot2 (>= 3.4.0), grDevices, HDcpDetect, ecp, kableExtra,
        lubridate, magrittr, mclust, rlang, stats, stringr, utils, zoo
Suggests: Biostrings, DT, dplyr, here, knitr, readxl, rmarkdown, R.rsp,
        testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr, R.rsp
NeedsCompilation: no
Packaged: 2026-05-27 18:20:05 UTC; vadim
Author: Vadim Tyuryaev [aut, cre] (ORCID:
    <https://orcid.org/0009-0008-1361-6265>),
  Jane Heffernan [aut],
  Hanna Jankowski [aut]
Maintainer: Vadim Tyuryaev <vadim.tyuryaev@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2026-05-30 13:40:21 UTC
Built: R 4.6.0; ; 2026-06-18 03:08:14 UTC; windows
