DESCRIPTION

Package: STdeconvolve
Type: Package
Title: Reference-free Cell-Type Deconvolution of Multi-Cellular Spatially
    Resolved Transcriptomics Data 
Version: 1.3.1
Authors@R:
    c(person(given = "Brendan",
           family = "Miller",
           role = c("aut", "cre"),
           email = "bmill3r@gmail.com",
           comment = c(ORCID = "0000-0002-9559-4045")),
           person(given = "Jean",
                  family = "Fan",
                  role = c("aut"),
                  email = "jeanfan@jhu.edu",
                  comment = c(ORCID = "0000-0002-0212-5451"))
    )
URL: https://jef.works/STdeconvolve/
BugReports: https://github.com/JEFworks-Lab/STdeconvolve/issues
Description: STdeconvolve as an unsupervised, reference-free approach to infer
    latent cell-type proportions and transcriptional profiles within
    multi-cellular spatially-resolved pixels from spatial transcriptomics (ST)
    datasets. STdeconvolve builds on latent Dirichlet allocation (LDA), a
    generative statistical model commonly used in natural language processing
    for discovering latent topics in collections of documents. In the context of
    natural language processing, given a count matrix of words in documents, LDA
    infers the distribution of words for each topic and the distribution of
    topics in each document. In the context of ST data, given a count matrix of
    gene expression in multi-cellular ST pixels, STdeconvolve applies LDA to
    infer the putative transcriptional profile for each cell-type and the
    proportional representation of each cell-type in each multi-cellular ST
    pixel.
biocViews: Transcriptomics, Visualization, RNASeq, Bayesian, Spatial, Software,
    GeneExpression
License: GPL-3
Encoding: UTF-8
LazyData: FALSE
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.1
Imports:
    topicmodels,
    BiocParallel,
    Matrix,
    methods,
    mgcv,
    ggplot2,
    scatterpie,
    viridis,
    slam,
    stats,
    clue,
    reshape2,
    graphics,
    grDevices,
    utils
Remotes:
    JEFworks/liger
Depends:
    R (>= 4.1)
Suggests: 
    knitr,
    BiocStyle,
    rmarkdown,
    testthat,
    rcmdcheck,
    gplots,
    gridExtra,
    hash,
    dplyr,
    parallel,
    magick
VignetteBuilder:
    knitr