Package: ZetaSuite 1.0.1

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.

Authors:Yajing Hao [aut], Shuyang Zhang [ctb], Junhui Li [cre], Guofeng Zhao [ctb], Xiang-Dong Fu [cph, fnd]

ZetaSuite_1.0.1.tar.gz
ZetaSuite_1.0.1.zip(r-4.5)ZetaSuite_1.0.1.zip(r-4.4)ZetaSuite_1.0.1.zip(r-4.3)
ZetaSuite_1.0.1.tgz(r-4.4-any)ZetaSuite_1.0.1.tgz(r-4.3-any)
ZetaSuite_1.0.1.tar.gz(r-4.5-noble)ZetaSuite_1.0.1.tar.gz(r-4.4-noble)
ZetaSuite_1.0.1.tgz(r-4.4-emscripten)ZetaSuite_1.0.1.tgz(r-4.3-emscripten)
ZetaSuite.pdf |ZetaSuite.html
ZetaSuite/json (API)

# Install 'ZetaSuite' in R:
install.packages('ZetaSuite', repos = c('https://junhuili1017.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • SVMcurve - The SVM curve lines in Zeta-plot.
  • ZseqList - The bin size for Zeta calculation.
  • countMat - Subsampled data from in-house HTS2 screening for global splicing regulators.
  • countMatSC - The cell x gene matrix from single-cell RNA-seq.
  • negGene - Input negative file.
  • nonExpGene - Input internal negative control file.
  • posGene - Input positive file.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 2 scripts 162 downloads 7 exports 81 dependencies

Last updated 3 years agofrom:4997735d8a. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 15 2024
R-4.5-winNOTEDec 15 2024
R-4.5-linuxNOTEDec 15 2024
R-4.4-winNOTEDec 15 2024
R-4.4-macNOTEDec 15 2024
R-4.3-winNOTEDec 15 2024
R-4.3-macNOTEDec 15 2024

Exports:EventCoverageFDRcutoffQCSVMZetaZetaSuitSCZscore

Dependencies:askpassbase64encbslibcachemclassclicolorspacecpp11crosstalkcurldata.tabledigestdplyre1071evaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegridExtragtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonlitekernlabknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemixtoolsmunsellnlmeopensslpillarpkgconfigplotlyplyrpromisesproxypurrrR6rappdirsRColorBrewerRcppreshape2rlangrmarkdownRtsnesassscalessegmentedstringistringrsurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

ZetaSuite

Rendered fromZetaSuite.Rmdusingknitr::rmarkdownon Dec 15 2024.

Last update: 2022-03-31
Started: 2022-03-31