stochasticProfilingData: User prompt for generation and visualization of synthetic...
In stochprofML: Stochastic Profiling using Maximum Likelihood Estimation
Description
Usage
Details
Value
Author(s)
References
View source: R/stochasticProfilingData.R
Description
Generation of a dataset of i.i.d measurements as considered in the stochastic profiling model. The user is prompted to input all required settings. He or she hence does not have to delve into the structure of this package.
Usage
1
Details
This function generates a dataset of i.i.d synthetic measurements as considered in the stochastic profiling model. The user is prompted to input all required settings, e.g. the exact model (LN-LN, rLN-LN or EXP-LN), the number of samples, the number of populations etc. The dataset is returned as a matrix and visualized in histograms together with the data generating probability density function (pdf).
Value
A matrix containing the synthetic data. Columns stand for different genes, rows for samples.
Author(s)
Lisa Amrhein, Christiane Fuchs
Maintainer: Lisa Amrhein <amrheinlisa@gmail.com>
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.
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Description Usage Details Value Author(s) References
View source: R/stochasticProfilingData.R
Description
Generation of a dataset of i.i.d measurements as considered in the stochastic profiling model. The user is prompted to input all required settings. He or she hence does not have to delve into the structure of this package.
Usage
1 |
Details
This function generates a dataset of i.i.d synthetic measurements as considered in the stochastic profiling model. The user is prompted to input all required settings, e.g. the exact model (LN-LN, rLN-LN or EXP-LN), the number of samples, the number of populations etc. The dataset is returned as a matrix and visualized in histograms together with the data generating probability density function (pdf).
Value
A matrix containing the synthetic data. Columns stand for different genes, rows for samples.
Author(s)
Lisa Amrhein, Christiane Fuchs
Maintainer: Lisa Amrhein <amrheinlisa@gmail.com>
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>
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