R: Analyze High-Dimensional High-Throughput Dataset and Quality Control Single-Cell RNA-Seq

# Analyze High-Dimensional High-Throughput Dataset and Quality Control Single-Cell RNA-Seq

## Documentation for package ‘ZetaSuite’ version 1.0.3

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

countMat | Subsampled data from in-house HTS2 screening for global splicing regulators.
countMatSC | The cell x gene matrix from single-cell RNA-seq.
EventCoverage | Generate event coverage analysis and visualization for alternative splicing data.
FDRcutoff | Determine optimal cutoff thresholds based on Screen Strength analysis.
negGene | Input negative file.
nonExpGene | Input internal negative control file.
posGene | Input positive file.
QC | Perform quality control analysis for high-throughput screening data.
SVM | Generate SVM decision boundaries for positive and negative control separation.
SVMcurve | The SVM curve lines in Zeta-plot.
Zeta | Calculation of zeta and weighted zeta score.
ZetaSuiteApp | Launch ZetaSuite Shiny Application
ZetaSuitSC | Calculate zeta score for single cell RNA-seq quality control.
Zscore | Z-score normalization for high-throughput screening data.
ZseqList | The bin size for Zeta calculation.