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countprop: Calculate Model-Based Metrics of Proportionality on Count-Based Compositional Data

This package allows estimation of several types of proportionality metrics for count-based compositional data such as 16S, metagenomic, and single-cell sequencing data. The package includes functions that allow standard empirical estimates of these proportionality metrics, as well as estimates based on the multinomial logit-normal model.

To install this package from github, run the following code:

if (!require(devtools)) {
  install.packages("devtools")
  library(devtools)
}
install_github("kevinmcgregor/countprop", dependencies=TRUE, build_vignettes=TRUE)

Once the package is loaded into R, you can view the vignette:

library(countprop)
vignette("countprop")

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Version

Install

install.packages('countprop')

Monthly Downloads

193

Version

1.0.1

License

GPL (>= 3)

Maintainer

Kevin McGregor

Last Published

August 18th, 2023

Functions in countprop (1.0.1)

naiveVariation

Naive (Empirical) Variation
ebicPlot

Extended Bayesian Information Criterion Plot
ebic

Extended Bayesian Information Criterion
logLik

Log-Likelihood
singlecell

Single cell sequencing data from mouse embryonic stem cells in G1 phase
pluginVariation

Plugin Variation
logitNormalVariation

Logit Normal Variation
mlePath

Maximum Likelihood Estimator Paths
mleLR

Maximum Likelihood Estimate for multinomial logit-normal model
logVarTaylorFull

Full logp Variance-Covariance