Function reference • nQuack

Preparing Data

Prepare your data for ploidal estimation with nQuack.

prepare_data(): Prepare data - Step 1

process_data(): Process data - Step 2

process_nquire(): Use nQuire's Data

denoise_data(): Denoise Data

Bclean(): Remove noise with the beta distribution

Simulating data

Simulate data for a given ploidal level.

sim.ind.BB(): Simulate Allele Counts for Single Individual - Beta-Binomial Distribution

sim.ind.BB.tau(): Simulate Allele Counts for Single Individual - Beta-Binomial Distribution with Overdispersion and Error

sim.ind.simple(): Simulate Allele Counts for Single Individual - Simple Approach

Basic Mixture Models

Wrapper functions to run model selection for diploids, triploids, tetraploids, pentaploids, and hexaploids.

quackNormal(): Model Selection - Expectation Maximization - Normal Mixture

quackNormalNQ(): Model Selection - Expectation Maximization - Normal Mixture (nQuire)

quackBeta(): Model Selection - Expectation Maximization - Beta Mixture

quackBetaBinom(): Model Selection - Expectation Maximization - Beta-Binomial Mixture

More on Mixture Models

Wrapper functions for model selection, running specific sets of mixture models, and bootstrap replication.

quackit(): Model Selection - Based on BIC or Log-Likelihood

bestquack(): Model Selection - Expectation Maximization - Choose your distribution and type

quackNboots(): Bootstrapping - Expectation Maximization - Choose your distribution and type

Expectation Maximization Base Functions

Functions used within our mixture models

emstepN(): Expectation maximization - Normal Distribution

emstepNU(): Expectation maximization - Normal and Uniform Distribution

emstepNA(): Expectation maximization - Normal Distribution

emstepNUA(): Expectation maximization - Normal Distribution

emstepB(): Expectation maximization - Beta Distribution

emstepBU(): Expectation maximization - Beta and Uniform Distributions

emstepBB(): Expectation maximization - Beta-Binomial Distribution

emstepBBU(): Expectation maximization - Beta-Binomial and Uniform Distributions

estepB3(): E-Step for Expectation Maximization - Beta + Beta + Beta Distribution

emstepB3(): Expectation maximization - Beta + Beta + Beta Distribution

Helper functions

Everything else.

alphabetacalc(): Calculate Alpha and Beta from Mean and Variance

alphabetacalctau(): Calculate Alpha and Beta from Mean, Tau, and Error rate.

alphabetacalcvec(): Vector-based - Calculate Alpha and Beta from Mean and Variance

alphabetacalctauvec(): Vector-based - Calculate Alpha and Beta from Mean, Tau, and Error rate.

muvarcalcvec(): Variance calculation from Mean, Tau, and Sequencing Error

process_rcpp(): Data Preparation - Matrix Filtering

nQuire_reformat(): Data Preparation - Use nQuire's Data

setconvert(): Calculate Variance from Mean, Tau, and Sequencing Error

resample_xm(): Calculate Alpha and Beta from Mean and Variance