Ineffective alternative feature selection methods based on the depth-adjusted negative binomial model. Functions tagged with "bg__" are not meant for direct usage and are not available in the Bioconductor release.
output from NBumiFitModel or NBumiFitBasicModel.
window for calculating the moving median.
Calculates dropout probability for each observation using depth-adjusted negative binomial means and dispersions calculated from a fitted power-law relationship between mean and dispersion. Total dropouts per gene are modelled using the normal approximation of the sum of bernoulli variables. And significance is evaluated using a Z-test.
obsolete__nbumiFeatureSelectionDropouts Ranks genes by significance of increase in dropouts compared to expectation allowing for gene-specific dispersions.
obsolete__nbumiFeatureSelectionHighVarDist2Med Ranks genes by the distance to median of log-transformed estimated dispersions.
Sorted vector of p-values/distances.
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library(M3DExampleData) #counts <- as.matrix(Mmus_example_list$data); #counts <- counts[rowSums(counts) > 0,]; #fit <- NBumiFitModel(counts); #Dropout_features <- names(obsolete__nbumiFeatureSelectionDropouts(fit)[1:2000]); #dist2med_features <- names(obsolete__nbumiFeatureSelectionHighVarDist2Med(fit)[1:2000]);
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