Learn R Programming

ZIBBSeqDiscovery (version 1.0)

Zero-Inflated Beta-Binomial Modeling of Microbiome Count Data

Description

Microbiome count data (Operational Taxonomic Unit, OTUs) is usually overdispersed and has excessive zero counts. The 'ZIBBSeqDiscovery' assumes a zero-inflated beta-binomial model for the distribution of the count data, and employes link functions to adjust interested covariates. To fit the model, two approaches are proposed (i) a free approach which treats the overdispersion parameters for OTUs as independent, and (ii) a constrained approach which proposes a mean-overdispersion relationship to the count data. This package can be used to test the association between the composition of the microbiome counts and the interested covariates.

Copy Link

Version

Install

install.packages('ZIBBSeqDiscovery')

Monthly Downloads

4

Version

1.0

License

GPL-2

Maintainer

Yi-Hui Zhou

Last Published

March 23rd, 2018

Functions in ZIBBSeqDiscovery (1.0)

free.loglikelihood

Define the objective function in optimization procedure for estimating parameters with free approach
ZIBBSeqDiscovery-package

ZIBBSeqDiscovery
mcc.adj

Using MCC method to replace NAs in the p values
fitZIBB

The main function to fit ZIBB model
kostic.x

Data set for ZIBBSeqDiscovery
constrained.estimate

Estimate parameters with constrained approach
constrained.loglikelihood

Define the objective function in optimization procedure for estimating parameters with constrained approach
regression

Simple linear regression
data.Y

Data set for ZIBBSeqDiscovery
kostic.y

Data set for ZIBBSeqDiscovery
free.estimate

Estimate parameters with free approach