CRAN/E | scModels

scModels

Fitting Discrete Distribution Models to Count Data

Installation

About

Provides functions for fitting discrete distribution models to count data. Included are the Poisson, the negative binomial, the Poisson-inverse gaussian and, most importantly, a new implementation of the Poisson-beta distribution (density, distribution and quantile functions, and random number generator) together with a needed new implementation of Kummer's function (also: confluent hypergeometric function of the first kind). Three different implementations of the Gillespie algorithm allow data simulation based on the basic, switching or bursting mRNA generating processes. Moreover, likelihood functions for four variants of each of the three aforementioned distributions are also available. The variants include one population and two population mixtures, both with and without zero-inflation. The package depends on the 'MPFR' libraries () which need to be installed separately (see description at ). This package is supplement to the paper "A mechanistic model for the negative binomial distribution of single-cell mRNA counts" by Lisa Amrhein, Kumar Harsha and Christiane Fuchs (2019) doi:10.1101/657619 available on bioRxiv.

System requirements gmp (>= 4.2.3), mpfr (>= 3.0.0)

Key Metrics

Version 1.0.4
R ≥ 3.1.0
Published 2023-01-24 470 days ago
Needs compilation? yes
License GPL-3
CRAN checks scModels results

Downloads

Yesterday 14 0%
Last 7 days 67 -32%
Last 30 days 270 +10%
Last 90 days 740 -24%
Last 365 days 3.262 -14%

Maintainer

Maintainer

Lisa Amrhein

amrheinlisa@gmail.com

Authors

Lisa Amrhein

aut / cre

Kumar Harsha

aut

Christiane Fuchs

aut

Pavel Holoborodko

ctb

(Author and copyright holder of 'mpreal.h')

Material

NEWS
Reference manual
Package source

In Views

Distributions

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

scModels archive

Depends

R ≥ 3.1.0

Imports

Rcpp
gamlss.dist

Suggests

knitr
rmarkdown
testthat

LinkingTo

Rcpp