R: Power and Sample Size Calculation for Differential Abundance Microbiome Studies

# Power and Sample Size Calculation for Differential Abundance Microbiome Studies

## Documentation for package ‘power.nb’ version 0.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

contour_plot_fun | Contour plot for showing predicted power
countdata_sim_fun | Simulate Count Data for Microbiome Studies
deseqfun | Estimate log fold changes using 'DESeq2'.
deseq_fun_est | Fold change and p-value estimations for simulations
dispersion_fit | Fit the non-linear function to dispersion estimates
dispersion_fun | Calculate Dispersion for Microbiome Data
dnormmix | Density of a Normal Mixture Model
dnormmix0 | Density function for the mixture of Gaussian distributions
filter_low_count | Filter to remove low abundant taxa
gam_fit | Title
genmixpars | generate normal mixture parameters (prob vector, mean vector, sd vector for a specified set of 'x' values (logmean)
gen_parnames | Generate Parameter Names for Mixture Model
logfoldchange_fit | Fit a mixture of Gaussian distributions to log fold change
logfoldchange_sim_fun | Simulate Log Fold Change Values
logmean_fit | Fit a mixture of Gaussian Distributions to log mean count of taxa.
logmean_sim_fun | Simulate Log Means for OTUs
myrnormmix | Simulating from a mixture of Gaussian
nllfun | Objective function
optimal.comp | Computes the optimal number of gaussian components for log mean count
polyfun | General-purpose log-likelihood function, vectorized sum(pars*x^i)
power_fun_ss | Fit a smooth power model for sample size estimation
read_data | Extract specified data from a list of datasets
rnormmix0 | general-purpose normal-mixture deviate generator: takes _matrices_ of probabilities, means, sds
sample_size_ss_interp | Estimate sample size required to achieve a target statistical power
ss_solver | Solve for the sample size required to achieve a target statistical power
uniroot_ss | Sample Size estimation function using uniroot