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

In stochprofML: Stochastic Profiling using Maximum Likelihood Estimation

Description

Maximum likelihood estimation for the parameters in the stochastic profiling model. The user is prompted to input the data and all required settings. He or she hence does not have to delve into the structure of this package.

Usage

stochasticProfilingML()

Details

The function performs maximum likelihood estimation for the parameters in the stochastic profiling model. The user is prompted to input the data and all required settings, i.e. especially the data, but also the exact model (LN-LN, rLN-LN or EXP-LN), the number of populations, the number of cells per sample etc. The data can either be entered manually, or it can be read from a file, or the user enters the name of a variable which contains the data.

Value

A list as returned by stochprof.loop, i.e. the following components:

mle	maximum likelihood estimate
neg-loglikeli	value of the negative log-likelihood function at maximum likelihood estimate
ci	approximate marginal maximum likelihood confidence intervals for the maximum likelihood estimate
pargrid	matrix containing parameter combinations and according values of the target function
bic	Bayesian information criterion value
adj.bic	adjusted Bayesian information criterion value which takes into account the numbers of parameters that were estimated during the preanalysis of a gene cluster. Is only calculated if parameter subgroups is given, otherwise set to NULL.
pen	penalization for densities not fulfilling required constraints. If use.constraints is FALSE, this has no practical meaning. If use.constraints is TRUE, this value is included in loglikeli.

Author(s)

Lisa Amrhein, Christiane Fuchs

Maintainer: Lisa Amrhein <[e-mail]>

References

"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 (* joint first authors, ^ joint last authors) <doi:10.1073/pnas.1311647111>

"Pheno-seq - linking visual features and gene expression in 3D cell culture systems" by Stephan M. Tirier, Jeongbin Park, Friedrich Preusser, Lisa Amrhein, Zuguang Gu, Simon Steiger, Jan-Philipp Mallm, Teresa Krieger, Marcel Waschow, Bjoern Eismann, Marta Gut, Ivo G. Gut, Karsten Rippe, Matthias Schlesner, Fabian Theis, Christiane Fuchs, Claudia R. Ball, Hanno Glimm, Roland Eils & Christian Conrad: Sci Rep 9, 12367 (2019) <doi:10.1038/s41598-019-48771-4>

stochprofML documentation built on July 1, 2020, 5:18 p.m.