NBumi_FSHighVar: Variance-based Feature Selection
In tallulandrews/M3D: Michaelis-Menten Modelling of Dropouts in single-cell RNASeq

Description Usage Arguments Details Value Examples

Ranks genes by residual dispersion from mean-dispersion power-law relationship.

1 2	NBumiFeatureSelectionHighVar(fit)

fit

output from NBumiFitModel or NBumiFitBasicModel.

Uses linear regression on log-transformed mean expression and fitted dispersions. Ranks genes by the residuals of this fit, negative = high variance, positive = low variance.

Sorted vector of residuals.

	library(M3DExampleData)
	counts <- NBumiConvertData(Mmus_example_list$data)
	fit <- NBumiFitModel(counts);
	HVGs <- names(NBumiFeatureSelectionHighVar(fit)[1:2000]);