ZetaSuite: Analyze High-Dimensional High-Throughput Dataset and Quality
Control 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: |
1.0.1 |
| Depends: |
R (≥ 2.10) |
| Imports: |
RColorBrewer, Rtsne, dplyr, e1071, ggplot2, reshape2, gridExtra, mixtools |
| Suggests: |
knitr, rmarkdown |
| Published: |
2022-05-24 |
| 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> |
| License: |
GPL-2 | GPL-3 |
| NeedsCompilation: |
no |
| CRAN checks: |
ZetaSuite results |
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