stochprofML: Stochastic Profiling using Maximum Likelihood Estimation
This is an R package accompanying the paper "Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles" by Sameer S Bajikar, Christiane Fuchs, Andreas Roller, Fabian J Theis and Kevin A Janes (PNAS 2014, 111(5), E626-635). In this paper, we measure expression profiles from small heterogeneous populations of cells, where each cell is assumed to be from a mixture of lognormal distributions. We perform maximum likelihood estimation in order to infer the mixture ratio and the parameters of these lognormal distributions from the cumulated expression measurements.
| Version: |
1.1 |
| Depends: |
R (≥ 2.0) |
| Imports: |
MASS, numDeriv |
| Published: |
2014-05-22 |
| Author: |
Christiane Fuchs |
| Maintainer: |
Christiane Fuchs <christiane.fuchs at helmholtz-muenchen.de> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
stochprofML results |
Downloads: