| 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 |