stochprofML: stochastic profiling using maximum likelihood estimation in R.
Lisa AmrheinChristiane FuchsPublished in: BMC bioinformatics (2021)
Stochastic profiling outweighs the necessary demixing of mixed samples with a saving in experimental cost and effort and less measurement error. It offers possibilities for parameterizing heterogeneity, estimating underlying pool compositions and detecting differences between cell populations between samples.