Package: ZetaSuite
Type: Package
Title: Analyze High-Dimensional High-Throughput Dataset and Quality
        Control Single-Cell RNA-Seq
Version: 1.0.2
Date: 2025-09-24
Authors@R: c(
    person(given = "Yajing", family = "Hao", email = "yahao@health.ucsd.edu", role  = c("aut"), comment = c(ORCID = "0000-0003-1384-4176")),
    person(given = "Shuyang", family = "Zhang", email = "s4zhang@ucsd.edu", role  = "ctb", comment=c(ORCID="0000-0002-8428-1828")),
    person(given = "Junhui", family = "Li", email = "ljh.biostat@gmail.com", role = "cre", comment=c(ORCID="0000-0003-3973-1700")),
    person(given = "Guofeng", family = "Zhao", email = "gzhao@health.ucsd.edu", role = "ctb"),
    person(given = "Xiang-Dong", family = "Fu", email = "xdfu@health.ucsd.edu", role = c("cph","fnd"), comment = c(ORCID = "0000-0001-5499-8732"))
		)
Maintainer: Junhui Li <ljh.biostat@gmail.com>
Description: The advent of genomic technologies has enabled the generation of two-dimensional or even multi-dimensional high-throughput data, e.g., monitoring multiple changes in gene expression in genome-wide siRNA screens across many different cell types (E Robert McDonald 3rd (2017) <doi: 10.1016/j.cell.2017.07.005> and Tsherniak A (2017) <doi: 10.1016/j.cell.2017.06.010>) or single cell transcriptomics under different experimental conditions. We found that simple computational methods based on a single statistical criterion is no longer adequate for analyzing such multi-dimensional data. We herein introduce 'ZetaSuite', a statistical package initially designed to score hits from two-dimensional RNAi screens.We also illustrate a unique utility of 'ZetaSuite' in analyzing single cell transcriptomics to differentiate rare cells from damaged ones (Vento-Tormo R (2018) <doi: 10.1038/s41586-018-0698-6>). In 'ZetaSuite', we  have the following steps: QC of input datasets, normalization using Z-transformation, Zeta score calculation and hits selection based on defined Screen Strength.
BugReports: https://github.com/JunhuiLi1017/ZetaSuite/issues
Imports: RColorBrewer, Rtsne, e1071, ggplot2, reshape2, gridExtra,
        mixtools, shinyjs, shinydashboard, shiny, plotly, DT
License: MIT + file LICENSE
Depends: R (>= 2.10)
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Author: Yajing Hao [aut] (ORCID: <https://orcid.org/0000-0003-1384-4176>),
  Shuyang Zhang [ctb] (ORCID: <https://orcid.org/0000-0002-8428-1828>),
  Junhui Li [cre] (ORCID: <https://orcid.org/0000-0003-3973-1700>),
  Guofeng Zhao [ctb],
  Xiang-Dong Fu [cph, fnd] (ORCID:
    <https://orcid.org/0000-0001-5499-8732>)
NeedsCompilation: no
Packaged: 2025-09-24 20:22:23 UTC; lij11
Repository: CRAN
Date/Publication: 2025-09-24 21:00:02 UTC
Encoding: UTF-8
Built: R 4.6.0; ; 2026-03-26 05:20:08 UTC; windows
