R: Variance Stabilizing Transformations for Single Cell UMI Data

# Variance Stabilizing Transformations for Single Cell UMI Data

## Documentation for package ‘sctransform’ version 0.4.3

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

clip_matrix_values | Clip matrix values to specified range
close_progress_bar | Close progress bar
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_formula | Extract model formula from model string
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
prepare_regressor_data | Prepare regressor data from vst object and cell attributes
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
setup_progress_bar | Setup progress bar for batch processing
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
update_progress_bar | Update progress bar
vst | Variance stabilizing transformation for UMI count data