runMPLNClust: Launch Shiny App For Package MPLNClust
In anjalisilva/MPLNClust: Mixtures of Multivariate Poisson-Log Normal Model for Clustering Count Data
runMPLNClust R Documentation
Launch Shiny App For Package MPLNClust
Description
A function that launches the shiny app for this package.
The shiny app permit to perform clustering using mixtures
of MPLN via variational-EM. Model selection is performed
using AIC, AIC3, BIC and ICL.
Usage
runMPLNClust()
Value
No return value but open up a shiny page.
Author(s)
Anjali Silva, anjali@alumni.uoguelph.ca
References
Silva, A. et al. (2019). A multivariate Poisson-log normal mixture model
for clustering transcriptome sequencing data. BMC Bioinformatics 20.
Link
Subedi, S., and R. Browne (2020). A parsimonious family of multivariate Poisson-lognormal
distributions for clustering multivariate count data. arXiv preprint arXiv:2004.06857.
Link
Examples
## Not run:
runMPLNClust()
## End(Not run)
anjalisilva/MPLNClust documentation built on Sept. 19, 2024, 7:34 a.m.
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| runMPLNClust | R Documentation |
Launch Shiny App For Package MPLNClust
Description
A function that launches the shiny app for this package. The shiny app permit to perform clustering using mixtures of MPLN via variational-EM. Model selection is performed using AIC, AIC3, BIC and ICL.
Usage
runMPLNClust()
Value
No return value but open up a shiny page.
Author(s)
Anjali Silva, anjali@alumni.uoguelph.ca
References
Silva, A. et al. (2019). A multivariate Poisson-log normal mixture model for clustering transcriptome sequencing data. BMC Bioinformatics 20. Link
Subedi, S., and R. Browne (2020). A parsimonious family of multivariate Poisson-lognormal distributions for clustering multivariate count data. arXiv preprint arXiv:2004.06857. Link
Examples
## Not run:
runMPLNClust()
## End(Not run)
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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