Package Description and Functionalities | Installation | Simulating microbiome data | Two ways to obtain parameters for data simulation using MixGaussSim | Dataset | Pre-filtering low abundant taxa | Fold change and Dispersion Estimation | Modeling the distribution of log mean counts | Modelling the distribution of log fold change estimates | Modelling the dispersion estimates | Simulate count microbiome data | Simulate log mean count and log fold change | Simulate counts from the negative binomial distribution | Comparing the distributions between simulated count d of mean count and fold change from simulation with actual data | Estimating Statistical Power for Individual Taxa | Estimate p-values associated with simulated fold changes | Fitting the Generalized Additive Model (GAM) | Contour plot showing power for various combinations of mean abundance and fold change | Sample size calculation | Simulate count data for various sample sizes | Estimate p-values associated to fold changes for each taxa for simulated data per sample size | Fit Generalized Additive Model (GAM) for power estimation | Estimate sample size for a given statistical power, fold change and mean abundance | Appendix | Data description and parameter estimates from actual microbiome datasets | Acknowledgments | References

Package Description and Functionalities | Installation | Simulating microbiome data | Two ways to obtain parameters for data simulation using MixGaussSim | Dataset | Pre-filtering low abundant taxa | Fold change and Dispersion Estimation | Modeling the distribution of log mean counts | Modelling the distribution of log fold change estimates | Modelling the dispersion estimates | Simulate count microbiome data | Simulate log mean count and log fold change | Simulate counts from the negative binomial distribution | Comparing the distributions between simulated count d of mean count and fold change from simulation with actual data | Estimating Statistical Power for Individual Taxa | Estimate p-values associated with simulated fold changes | Fitting the Generalized Additive Model (GAM) | Contour plot showing power for various combinations of mean abundance and fold change | Sample size calculation | Simulate count data for various sample sizes | Estimate p-values associated to fold changes for each taxa for simulated data per sample size | Fit Generalized Additive Model (GAM) for power estimation | Estimate sample size for a given statistical power, fold change and mean abundance | Appendix | Data description and parameter estimates from actual microbiome datasets | Acknowledgments | References