CalculateRogue: ROGUE calculation

In RyanYip-Kat/yipCat: Some function like ArchR style in Seurat Object

Description

Using ROGUE to assess the purity of single cell population.

Usage

CalculateRogue(.x, platform = NULL, cutoff = 0.05, k = NULL, features = NULL)

Arguments

.x	A tibble object returned from the SE_fun or entropy_fit function.
platform	The platform ("UMI" or "full-length") used for generating the tested dataset.
cutoff	The threshold (adjusted P value) for identifying significant ds. The default threshold is 0.05.
k	The scaling factor for calculating ROGUE. The default value of K is set to 45 and 500 for droplet-based ("UMI") and "full-length" based datasets, respectively. When specifying a custom k value, the "platform" argument is redundant.
features	Use these features to calculate ROGUE.

Details

By taking advantage of the wide applicability of S-E model to scRNA-seq data, we introduce the statistic ROGUE to measure the purity of a cell population as:

ROGUE=1-∑sig.ds/(∑sig.ds+K)

where K is an important parameter that constrains the ROGUE value between 0 and 1. A cell population with no significant ds for all genes will receive a ROGUE value of 1, while a population with maximum summarization of significant ds is supposed to yield a purity score of ~0.

Value

A value of ROGUE.

Examples

ent.res <- SE_fun(expr, span = 0.1, r = 1, mt.method = "fdr")
CalculateRogue(ent.res, platform = "UMI")
CalculateRogue(ent.res, k = 30)

RyanYip-Kat/yipCat documentation built on Dec. 18, 2021, 11:55 a.m.