Zeta: Calculation of zeta and weighted zeta score.

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

Calculation of zeta and weighted zeta score.

Description

This step calculates the Zeta Score based on the two curvecs. Firstly, this step provides another curve above the SVM curve to set a value to represent the regulatory function of gene i. Then, the area between the two curves (the one mentioned above and the SVM curve) is calculated as the Zeta score for this gene. Since the graph of the curves is divided into m bins, then the Zeta score can be calculated as the sum of all the bins' areas that exist between the two curves.

Usage

Zeta(ZscoreVal, ZseqList, SVMcurve = NULL, SVM = FALSE)

Arguments

ZscoreVal	input file name.
ZseqList	the list of bins.
SVMcurve	SVM curves for decrease and increase direction.###not always use
SVM	do SVM or not, default is FALSE

Value

A data.frame where zeta values for all tested knockding-down genes including positive and negative controls. The first column is the direction which knockding-down gene will lead to exon inclusion, whereas the second column is the knock-down genes will lead to exon skipping.

Author(s)

Yajing Hao, Shuyang Zhang, Junhui Li, Guofeng Zhao, Xiang-Dong Fu

Examples

data(ZseqList)
data(SVMcurve)
data(countMat)
data(negGene)
ZscoreVal <- Zscore(countMat,negGene)
zetaData <- Zeta(ZscoreVal,ZseqList,SVM=FALSE)

ZetaSuite documentation built on May 25, 2022, 9:05 a.m.