rankDist: Identify the best rank cut-off for significant CpGs.

View source: R/rankDist.R

rankDistR Documentation

Identify the best rank cut-off for significant CpGs.

Description

Automated rank cut-off estimator for input CpGs.

Usage

rankDist(ranks, draw_intersects, noise_perc, mode, return.plot)

Arguments

ranks

getPCRanks output data frame.

draw_intersects

T/F whether to draw intersect lines if return.plot=T

noise_perc

Automatic=0.5, numeric between 0 and 1. Fraction of ranks to use to model the background noise. Not recommended to play with this value. Increasing/decreasing returns a looser/stricter threshold, respectively.

mode

"intersect" or "strict", determine cut-off with "intersect" or "strict" method. "Strict" is recommended for sets with lower variability

return.plot

T/F, whether to return a plot or a numeric

Value

If return.plot=T, a grob plotting the estimated cutoff on a plot of absolute eigenvector score vs. absolute rank order is returned. Otherwise, a numeric of the estimated cut-off is returned.

Examples

ranks <- getPCRanks(eigen, IDs = c("trt", "ctl"), PC = 1)
rankDist(ranks, mode="intersect")

PCBS documentation built on Sept. 11, 2024, 6:11 p.m.

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