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.

AuthorChristiane Fuchs
Date of publication2014-10-18 06:28:46
MaintainerChristiane Fuchs <christiane.fuchs@helmholtz-muenchen.de>
LicenseGPL (>= 2)
Version1.2

View on CRAN

Man pages

analyze.sod2: Analysis of SOD2 data in stochastic profiling model

analyze.toycluster: Analysis of toyclusters in stochastic profiling model

calculate.ci.EXPLN: Maximum likelihood confidence intervals for EXP-LN model

calculate.ci.LNLN: Maximum likelihood confidence intervals for LN-LN model

calculate.ci.rLNLN: Maximum likelihood confidence intervals for rLN-LN model

comb.summands: Combinations of fixed number of summands with pre-defined...

d.sum.of.mixtures.EXPLN: Sums of mixtures of zero, one or more lognormal random...

d.sum.of.mixtures.LNLN: Sums of mixtures of lognormal random variables

d.sum.of.mixtures.rLNLN: Sums of mixtures of lognormal random variables

generate.toydata: Generation and analysis of synthetic data in stochastic...

penalty.constraint.EXPLN: Penalization for population densities that do not fulfil...

penalty.constraint.LNLN: Penalization for population densities that do not fulfil...

penalty.constraint.rLNLN: Penalization for population densities that do not fulfil...

sod2: Measurements from the detoxifying enzyme, SOD2

stochasticProfilingData: User prompt for generation and visualization of synthetic...

stochasticProfilingML: User prompt for maximum likelihood estimation of stochastic...

stochprof.loop: Maximum likelihood estimation for the parameters in the...

stochprofML-package: Stochastic Profiling using Maximum Likelihood Estimation

stochprof.results.EXPLN: Evaluation of results from estimation of EXP-LN model

stochprof.results.LNLN: Evaluation of results from estimation of LN-LN model

stochprof.results.rLNLN: Evaluation of results from estimation of rLN-LN model

stochprof.search.EXPLN: Calculation of the log likelihood function of the EXP-LN...

stochprof.search.LNLN: Calculation of the log likelihood function of the LN-LN model

stochprof.search.rLNLN: Calculation of the log likelihood function of the rLN-LN...

toycluster.EXPLN: Synthetic data from the EXP-LN model

toycluster.LNLN: Synthetic data from the LN-LN model

toycluster.rLNLN: Synthetic data from the rLN-LN model

Files in this package

stochprofML
stochprofML/NAMESPACE
stochprofML/data
stochprofML/data/sod2.rda
stochprofML/data/toycluster.EXPLN.rda
stochprofML/data/toycluster.LNLN.rda
stochprofML/data/toycluster.rLNLN.rda
stochprofML/R
stochprofML/R/stochprof.logit.R stochprofML/R/d.sum.of.types.rLNLN.R stochprofML/R/stochprof.search.LNLN.R stochprofML/R/d.sum.of.types.LNLN.R stochprofML/R/r.sum.of.mixtures.EXPLN.R stochprofML/R/lognormal.exp.convolution.R stochprofML/R/get.range.rLNLN.R stochprofML/R/d.sum.of.mixtures.EXPLN.R stochprofML/R/calculate.ci.rLNLN.R stochprofML/R/comb.summands.R stochprofML/R/get.range.EXPLN.R stochprofML/R/r.sum.of.mixtures.LNLN.R stochprofML/R/generate.toydata.R stochprofML/R/stochasticProfilingML.R stochprofML/R/penalty.constraint.EXPLN.R stochprofML/R/r.sum.of.mixtures.rLNLN.R stochprofML/R/d.sum.of.mixtures.rLNLN.R stochprofML/R/analyze.sod2.R stochprofML/R/stochprof.results.EXPLN.R stochprofML/R/d.sum.of.lognormal.types.R stochprofML/R/stochprof.expit.R stochprofML/R/draw.parameters.rLNLN.R stochprofML/R/d.sum.of.lognormals.R stochprofML/R/calculate.ci.EXPLN.R stochprofML/R/stochprof.loop.R stochprofML/R/stochprof.results.rLNLN.R stochprofML/R/stochprof.results.LNLN.R stochprofML/R/transform.par.EXPLN.R stochprofML/R/draw.parameters.EXPLN.R stochprofML/R/backtransform.par.EXPLN.R stochprofML/R/get.range.LNLN.R stochprofML/R/penalty.constraint.LNLN.R stochprofML/R/d.sum.of.exp.types.R stochprofML/R/transform.par.rLNLN.R stochprofML/R/stochprof.search.EXPLN.R stochprofML/R/analyze.toycluster.R stochprofML/R/stochprof.search.rLNLN.R stochprofML/R/stochasticProfilingData.R stochprofML/R/transform.par.LNLN.R stochprofML/R/backtransform.par.rLNLN.R stochprofML/R/d.sum.of.mixtures.LNLN.R stochprofML/R/penalty.constraint.rLNLN.R stochprofML/R/set.model.functions.R stochprofML/R/calculate.ci.LNLN.R stochprofML/R/backtransform.par.LNLN.R stochprofML/R/draw.parameters.LNLN.R stochprofML/R/stochprofML-internal.R
stochprofML/MD5
stochprofML/DESCRIPTION
stochprofML/man
stochprofML/man/stochasticProfilingData.Rd stochprofML/man/calculate.ci.EXPLN.Rd stochprofML/man/toycluster.LNLN.Rd stochprofML/man/generate.toydata.Rd stochprofML/man/calculate.ci.rLNLN.Rd stochprofML/man/stochprof.results.EXPLN.Rd stochprofML/man/calculate.ci.LNLN.Rd stochprofML/man/stochprofML-package.Rd stochprofML/man/penalty.constraint.EXPLN.Rd stochprofML/man/stochasticProfilingML.Rd stochprofML/man/stochprof.search.EXPLN.Rd stochprofML/man/toycluster.EXPLN.Rd stochprofML/man/penalty.constraint.LNLN.Rd stochprofML/man/d.sum.of.mixtures.EXPLN.Rd stochprofML/man/d.sum.of.mixtures.LNLN.Rd stochprofML/man/toycluster.rLNLN.Rd stochprofML/man/stochprof.results.LNLN.Rd stochprofML/man/stochprof.search.rLNLN.Rd stochprofML/man/comb.summands.Rd stochprofML/man/analyze.sod2.Rd stochprofML/man/stochprof.loop.Rd stochprofML/man/d.sum.of.mixtures.rLNLN.Rd stochprofML/man/penalty.constraint.rLNLN.Rd stochprofML/man/analyze.toycluster.Rd stochprofML/man/stochprof.results.rLNLN.Rd stochprofML/man/sod2.Rd stochprofML/man/stochprof.search.LNLN.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.