Package: tTEscanR
Title: A user-friendly integrative R package for quantifying and
        visualizing translation efficiency from sequencing data in
        diverse biological systems
Version: 0.99.2
Authors@R: 
    c(
    person("Ana", "Varas-Sánchez", 
        email = "ana.varas@scilifelab.se", 
        role = c("aut", "cre"),
        comment = c(ORCID = "0009-0006-0187-8968")),
    person("Carlos", "Gallardo-Dodd",
        email = "carlos.gallardo@scilifelab.se",
        role = c("aut"),
        comment = c(ORCID = "0000-0002-6086-0550")),
    person("William", "Gao",
        email = "william.gao@pennmedicine.upenn.edu",
        role = c("aut"),
        comment = c(ORCID = "0000-0002-9415-331X")),
    person("Claudia", "Kutter",
        email = "claudia.kutter@ki.se",
        role = c("ths"),
        comment = c(ORCID = "0000-0002-8047-0058")),
    person("Karolinska Institutet",
        role = c("fnd"),
        comment = c(grant_id = "KID-2021-00308, KID-2023-01298")),
    person("Swedish Research Council",
        role = c("fnd"),
        comment = c(grant_id = "2023-02780")),
    person("Cancerfonden",
        role = c("fnd"),
        comment = c(grant_id = "22 2246 Pj, 25 4703 Pj"))
    )
Description: Translation elongation is dependent on codon-anticodon interactions, 
    with suitable nucleotide pairing being essential for efficient translation. 
    To quantify this relationship, we previously developed a computational pipeline 
    (GitHub - wgao688/sc_tRNA_mRNA) that uses mRNA codon usage relative to tRNA anticodon 
    availability as a proxy for theoretical translation efficiency (tTE). Here, we introduce 
    tTEscanR, a powerful  and user-friendly R-based package that extends this approach to 
    quantify translation efficiency from both bulk and single-cell sequencing data. tTEscanR 
    is a versatile tool for exploring translation efficiency in diverse cellular processes, 
    disease mechanisms, and therapeutic development. It also features an advanced visualization 
    module to generate high-quality plots, enhancing result interpretation and communication.
License: MIT + file LICENSE
Imports: stats, SummarizedExperiment, Biostrings, S4Vectors,
        MultiAssayExperiment, Matrix, DESeq2, matrixStats, tibble,
        dplyr, tRNAscanImport, GenomicRanges, Signac, utils, biomaRt,
        stringr, ggplot2, ggrepel, uwot, Rtsne, dendsort, grid,
        ComplexHeatmap, viridis, tidyr, ggpubr, patchwork, purrr,
        magrittr, rlang
Encoding: UTF-8
Depends: R (>= 4.6.0)
VignetteBuilder: knitr
URL: https://github.com/avarassanchez/tTEscanR
BugReports: https://github.com/avarassanchez/tTEscanR/issues
Suggests: testthat, withr, mockery, knitr, rmarkdown, BiocStyle,
        devtools, pheatmap, Seurat, IRanges, GenomeInfoDb, Rsamtools
Config/testthat/edition: 3
biocViews: Software, Epitranscriptomics, Transcriptomics,
        GeneExpression, GeneRegulation, Sequencing, SingleCell,
        CellBasedAssays
Roxygen: list(markdown = TRUE, r6 = FALSE)
Config/roxygen2/version: 8.1.1
git_url: https://git.bioconductor.org/packages/tTEscanR
git_branch: devel
git_last_commit: 81c5457
git_last_commit_date: 2026-10-16
Repository: Bioconductor 3.24
Date/Publication: 2026-11-04
NeedsCompilation: no
Packaged: 2026-11-05 02:11:03 UTC; biocbuild
Author: Ana Varas-Sánchez [aut, cre] (ORCID:
    <https://orcid.org/0009-0006-0187-8968>),
  Carlos Gallardo-Dodd [aut] (ORCID:
    <https://orcid.org/0000-0002-6086-0550>),
  William Gao [aut] (ORCID: <https://orcid.org/0000-0002-9415-331X>),
  Claudia Kutter [ths] (ORCID: <https://orcid.org/0000-0002-8047-0058>),
  Karolinska Institutet [fnd] (grant_id: KID-2021-00308, KID-2023-01298),
  Swedish Research Council [fnd] (grant_id: 2023-02780),
  Cancerfonden [fnd] (grant_id: 22 2246 Pj, 25 4703 Pj)
Maintainer: Ana Varas-Sánchez <ana.varas@scilifelab.se>
