FDRcutoff: Find a cut-off according to screen strength.

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

Find a cut-off according to screen strength.

Description

Find a cutoff according to the Screen Strength (SS) and graph the Screen Strength plot. Zeta score is used to rank genes, and then, SS is calculated to define a suitable cutoff so that the cutoff can define hits at different confidence intervals. Formula of SS: SS = 1 - aFDR/bFDR, where aFDR (apparent FDR) = number of non-expressors identified at hits divided by the total number of hits, bFDR (baseline FDR) = total number of non-expressors divided by all screened genes. SS plot labels: x-axis: zeta score, y-axis: Screen Strength, SS value is determined at each bin (m bin in total), then connect individual SS value to generate a simulated SS curve based on balance points. Users may choose one or multiple balance point as the different SS intervals.

Usage

FDRcutoff(zetaData, negGene, posGene, nonExpGene, combine = FALSE)

Arguments

zetaData	ZetaScore file calculated by ZetaSuite.
negGene	negative control dataset, the siRNAs/genes used as negative controls in screening.
posGene	positive control dataset, the siRNAs/genes used as positive controls in screening.
nonExpGene	non-expressed gene
combine	combine two direction zeta together(TRUE or FALSE),default FALSE

Value

A list of data.frame and plots, the data.frame is cut off matrix with 6 columns including "Cut_Off","aFDR", "SS","TotalHits","Num_nonExp" and "Type". Plots includes 'Zeta_type' and 'SS_cutOff'.

Author(s)

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

Examples

data(nonExpGene)
data(negGene)
data(posGene)
data(ZseqList)
data(countMat)
ZscoreVal <- Zscore(countMat,negGene)
zetaData <- Zeta(ZscoreVal,ZseqList,SVM=FALSE)
cutoffval <- FDRcutoff(zetaData,negGene,posGene,nonExpGene,combine=TRUE)

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