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: 1.2
Depends: R (≥ 2.0)
Imports: MASS, numDeriv
Published: 2014-10-18
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

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Reference manual: stochprofML.pdf
Package source: stochprofML_1.2.tar.gz
Windows binaries: r-devel: stochprofML_1.2.zip, r-release: stochprofML_1.2.zip, r-oldrel: stochprofML_1.2.zip
OS X Mavericks binaries: r-release: stochprofML_1.2.tgz, r-oldrel: stochprofML_1.2.tgz
Old sources: stochprofML archive

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