Comprehensive Automatized Evaluation of Distribution Models for Count Data

A large number of measurements generate count data. This is a statistical data type that only assumes non-negative integer values and is generated by counting. Typically, counting data can be found in biomedical applications, such as the analysis of DNA double-strand breaks. The number of DNA double-strand breaks can be counted in individual cells using various bioanalytical methods. For diagnostic applications, it is relevant to record the distribution of the number data in order to determine their biomedical significance (Roediger, S. et al., 2018. Journal of Laboratory and Precision Medicine. ). The software offers functions for a comprehensive automated evaluation of distribution models of count data. In addition to programmatic interaction, a graphical user interface (web server) is included, which enables fast and interactive data-scientific analyses. The user is supported in selecting the most suitable counting distribution for his own data set.

countfitteR

countfitteR is a web server based on Shiny technology for selecting the most appropriate count distribution in provided data sets.

Installation

countfitteR is available on CRAN.

install.packages("countfitteR")

However, you can also install the developmental version of countfitteR directly from GitHub

devtools::install_github("BioGenies/countfitteR")

Run countfitteR

To run countfitteR type the following command into an R console.

countfitteR::countfitteR_gui()

How to cite

• Chilimoniuk, J., Gosiewska, A., Słowik, J., Weiss, R., Deckert, P.M., Rödiger, S., and Burdukiewicz, M. (2021). countfitteR: efficient selection of count distributions to assess DNA damage. Annals of Translational Medicine.
• Chilimoniuk, J., Gosiewska, A., Słowik, J., Weiss, R., Deckert, P.M., Rödiger, S., Burdukiewicz, M., (2021). countfitteR: efficient selection of count distributions to assess DNA damage. Annals of Translational Medicine. https://doi.org/10.21037/atm-20-6363

@Article{,
  author = "Jarosław Chilimoniuk and Alicja Gosiewska and Jadwiga Słowik and Romano Weiss and P. Markus Deckert and Stefan Rödiger and Michał Burdukiewicz",
  title = "countfitteR: efficient selection of count distributions to assess DNA damage",
  year = 2021, 
  issn = {2305-5847},
  journal = "Annals of Translational Medicine",
  url = "https://atm.amegroups.org/article/view/63994/html",
}

@article{chilimoniuk_countfitter_2021,
	title = {{countfitteR}: efficient selection of count distributions to assess {DNA} damage},
	volume = {0},
	issn = {2305-5847, 2305-5839},
	shorttitle = {{countfitteR}},
	url = {https://atm.amegroups.org/article/view/63994/html},
	doi = {10.21037/atm-20-6363},
	abstract = {countfitteR: efficient selection of count distributions to assess DNA damage},
	language = {en},
	number = {0},
	urldate = {2021-03-15},
	journal = {Annals of Translational Medicine},
	author = {Chilimoniuk, Jarosław and Gosiewska, Alicja and Słowik, Jadwiga and Weiss, Romano and Deckert, P. Markus and Rödiger, Stefan and Burdukiewicz, Michał},
	month = mar,
	year = {2021},
	note = {Number: 0
Publisher: AME Publishing Company}
}