compRatio: Cubic spline logistic regression

In kdkorthauer/MADGiC: Fits an empirical Bayesian hierarchical model to obtain posterior probabilities that each gene is a driver.

Description

Performs the cubic spline logistic regression for use in the locfdr function

Usage

  compRatio(center, succ, fail, df = 5)

Arguments

center	numeric vector of the midpoints of the bins
succ	numeric vector of the same length of center that corresponds to the number of 'successes' (fulls) in each bin
fail	umeric vector of the same length of center that corresponds to the number of 'failures' (nulls) in each bin
df	the number of degrees of freedom for the spline regression (defaults to 5)

Value

list object with four elements:

z	numeric vector of midpoints
probs	numeric vector of fitted probabilities of success
ratio	numeric vector of the ratio of successes to failures, accounting for total numbers of successes and failures
df	the number of degrees of freedom used for the spline regression

Note

This internal function is not intended to be called by the user.

kdkorthauer/MADGiC documentation built on June 13, 2020, 1:35 p.m.