fdrtool.quantile: P-values estimation

In jmonlong/PopSV: Population-based detection of structural variants from Read-Depth signal

Description

Compute the null variances. The Z-score distribution is modeled as a Normal centered in 0. The variance is fitted at different level of tail-trimming.

Usage

fdrtool.quantile(z, quant.int = seq(0.4, 1, 0.02), z.th = NULL)

Arguments

z	a vector with the Z-scores
quant.int	a vector with the quantiles to test for the estimation of the null normal variance.
z.th	the Z-score threshold to use to estimate the null normal variance, if 'quant.int=NULL'. If one value the same threshold is used for both duplication and deletion; if a vector, the threshold for duplication / deletions.

Value

a list with

sigma.est.dup	the estimated null distribution variance for positive Z-scores
sigma.est.del	the estimated null distribution variance for negative Z-scores

Author(s)

Jean Monlong

jmonlong/PopSV documentation built on Sept. 15, 2019, 9:29 p.m.