Package index
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prepare_data() - Prepare data - Step 1
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process_data() - Process data - Step 2
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process_nquire() - Use nQuire's Data
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denoise_data() - Denoise Data
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Bclean() - Remove noise with the beta distribution
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sim.ind.BB() - Simulate Allele Counts for Single Individual - Beta-Binomial Distribution
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sim.ind.BB.tau() - Simulate Allele Counts for Single Individual - Beta-Binomial Distribution with Overdispersion and Error
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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.
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quackNormal() - Model Selection - Expectation Maximization - Normal Mixture
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quackNormalNQ() - Model Selection - Expectation Maximization - Normal Mixture (nQuire)
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quackBeta() - Model Selection - Expectation Maximization - Beta Mixture
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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.
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quackit() - Model Selection - Based on BIC or Log-Likelihood
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bestquack() - Model Selection - Expectation Maximization - Choose your distribution and type
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quackNboots() - Bootstrapping - Expectation Maximization - Choose your distribution and type
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emstepN() - Expectation maximization - Normal Distribution
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emstepNU() - Expectation maximization - Normal and Uniform Distribution
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emstepNA() - Expectation maximization - Normal Distribution
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emstepNUA() - Expectation maximization - Normal Distribution
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emstepB() - Expectation maximization - Beta Distribution
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emstepBU() - Expectation maximization - Beta and Uniform Distributions
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emstepBB() - Expectation maximization - Beta-Binomial Distribution
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emstepBBU() - Expectation maximization - Beta-Binomial and Uniform Distributions
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estepB3() - E-Step for Expectation Maximization - Beta + Beta + Beta Distribution
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emstepB3() - Expectation maximization - Beta + Beta + Beta Distribution
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alphabetacalc() - Calculate Alpha and Beta from Mean and Variance
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alphabetacalctau() - Calculate Alpha and Beta from Mean, Tau, and Error rate.
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alphabetacalcvec() - Vector-based - Calculate Alpha and Beta from Mean and Variance
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alphabetacalctauvec() - Vector-based - Calculate Alpha and Beta from Mean, Tau, and Error rate.
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muvarcalcvec() - Variance calculation from Mean, Tau, and Sequencing Error
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process_rcpp() - Data Preparation - Matrix Filtering
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nQuire_reformat() - Data Preparation - Use nQuire's Data
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setconvert() - Calculate Variance from Mean, Tau, and Sequencing Error
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resample_xm() - Calculate Alpha and Beta from Mean and Variance