Variance Stabilizing Transformations for Single Cell UMI Data

Documentation for package ‘sctransform’ version 0.4.1

compare_expression	Compare gene expression between two groups
correct	Correct data by setting all latent factors to their median values and reversing the regression model
correct_counts	Correct data by setting all latent factors to their median values and reversing the regression model
diff_mean_test	Non-parametric differential expression test for sparse non-negative data
diff_mean_test_conserved	Find differentially expressed genes that are conserved across samples
generate	Generate data from regularized models.
get_model_var	Return average variance under negative binomial model
get_nz_median2	Get median of non zero UMIs from a count matrix
get_residuals	Return Pearson or deviance residuals of regularized models
get_residual_var	Return variance of residuals of regularized models
is_outlier	Identify outliers
make.sparse	Convert a given matrix to dgCMatrix
pbmc	Peripheral Blood Mononuclear Cells (PBMCs)
plot_model	Plot observed UMI counts and model
plot_model_pars	Plot estimated and fitted model parameters
robust_scale	Robust scale using median and mad
robust_scale_binned	Robust scale using median and mad per bin
row_gmean	Geometric mean per row
row_var	Variance per row
smooth_via_pca	Smooth data by PCA
umify	Quantile normalization of cell-level data to match typical UMI count data
umify_data	Transformation functions for umify
vst	Variance stabilizing transformation for UMI count data