hc_cal: This function calculates the higher criticism

In mqzhanglab/wHC: Goodness of fit Statistics Calculation based on weighted p-values

This function calculates the higher criticism

Description

For ordered p-values p(1)<p(2)<...<p(n).Define Sn(t)=sum_i=1^n 1_p_(i)<=t. Then define the statistic T as T=(Sn(p(i))-n x p(i))/sqrt(n x p(i) x (1-p(i))). The higher criticism is calculated with HCmax=max T_(i). where 0<i<=(t0ratio x n)

Usage

hc_cal(pm, t0ratio = 1, filter = 0)

Arguments

pm	is a statistics matrix of P-values or weighted pvalues, each row represents a gene (independent tests) and each column represents a dataset (e.g. a permutation or an observation). Pm are not encouraged to have only 1 rows, if that happend, warning massage will produced.
t0ratio	is the ratio for the region c(0,t0ratio) of pvalues for statistic calculation.
filter	is the threshold to exclude extremely small pvalues to avoid them driving all signals.default 0.

Value

a numeric vector with each elements is a Higher criticism values calculated from each colum of the Pm

References

Donoho, D., & Jin, J. (2004). Higher Criticism for Detecting Sparse Heterogeneous Mixtures. The Annals of Statistics, 32(3), 962–994.

Examples

pval=matrix(runif(200,0,1),ncol=4,nrow=50)
w0=seq(0.5,1.5,length=50)
pwval=cal_cdf(pval,w=w0)
hc_cal(pwval,t0ratio=0.4)

mqzhanglab/wHC documentation built on April 1, 2022, 6:28 p.m.