ZetaSuite: Analyze High-Dimensional High-Throughput Dataset and QualityControl Single-Cell RNA-Seq
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.
| Version: | 1.0.2 |
| Depends: | R (≥ 2.10) |
| Imports: | RColorBrewer,Rtsne,e1071,ggplot2,reshape2,gridExtra,mixtools,shinyjs,shinydashboard,shiny,plotly,DT |
| Suggests: | knitr,rmarkdown |
| Published: | 2025-09-24 |
| DOI: | 10.32614/CRAN.package.ZetaSuite |
| Author: | Yajing Hao [aut], Shuyang Zhang [ctb], Junhui Li [cre], Guofeng Zhao [ctb], Xiang-Dong Fu [cph, fnd] |
| Maintainer: | Junhui Li <ljh.biostat at gmail.com> |
| BugReports: | https://github.com/JunhuiLi1017/ZetaSuite/issues |
| License: | MIT + fileLICENSE |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | ZetaSuite results |
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