ratiometric.binom.power: calculates the power in a binomial power model for...

In KarchinLab/cancerSeqStudy: Power and False Positive Analysis of Cancer Sequencing Studies

Description

calculates the power in a binomial power model for ratio-metric approach

Usage

ratiometric.binom.power(p, N, mu, Df = 1, Leff = 1500 * 3/4, r = 0.02,
  signif.level = 5e-06, nonsil.frac = 3/4)

Arguments

p	background proportion of total mutations falling into specific category
N	vector of sample sizes
mu	per base rate of mutation
Df	fraction of driver mutations that are the specific one of interest
Leff	effective gene length in bases (Length*nonsil.frac)
r	effect size for power analysis
signif.level	alpha level for power analysis
nonsil.frac	fraction of mutations which are non-silent

Value

vector containing power for each sample size

KarchinLab/cancerSeqStudy documentation built on May 8, 2019, 4:47 p.m.