stochasticProfilingData: User prompt for generation and visualization of synthetic...
In lisaamrhein/stochprofML: Stochastic Profiling using Maximum Likelihood Estimation
View source: R/stochasticProfilingData.R
stochasticProfilingData R Documentation
User prompt for generation and visualization of synthetic data in stochastic profiling model
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
stochasticProfilingData()
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>
lisaamrhein/stochprofML documentation built on June 1, 2024, 10:41 p.m.
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View source: R/stochasticProfilingData.R
| stochasticProfilingData | R Documentation |
User prompt for generation and visualization of synthetic data in stochastic profiling model
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
stochasticProfilingData()
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>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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