The goal of PsiNorm is to normalize a raw count matrix of expression genes profiles thanks to the sample specific Pareto shape parameter. The function first computes the cell specific shape parameter alpha of the Pareto distribution and then normalizes the samples with it. It estimates the parameter alpha by maximum likelihood, equal to the log geometric mean of the pseudo-sample. The Pareto parameter is inversely proportional to the sequencing depth, it is sample specific and its estimate is performed for each cell independently.
You can install the released version of PsiNorm with:
remotes::install_github("MatteoBlla/PsiNorm")
See the vignette for example usage.