An R package for analysis of microbiome relative abundance data using zero inflated beta GAMLSS and meta-analysis across microbiome studies using random effects models
Thanks for developing the approaches and user-friendly functions in the metamicrobiomeR package. This is quite impressive!
I have a question on the appropriate probability distribution to use in GAMLSS for relative abundance estimation and testing after zero replacement and CLR transformation. After the replacement and transformation, would I expect to have few/no zeros and negative values? If so, would you still recommend using the BEZI family? Or would you then perhaps recommend also using propmed.rel = "lm" in the taxa.compare function (or fitting the model in GAMLSS assuming a different distribution for the response)?
Hi Nhan,
Thanks for developing the approaches and user-friendly functions in the metamicrobiomeR package. This is quite impressive!
I have a question on the appropriate probability distribution to use in GAMLSS for relative abundance estimation and testing after zero replacement and CLR transformation. After the replacement and transformation, would I expect to have few/no zeros and negative values? If so, would you still recommend using the BEZI family? Or would you then perhaps recommend also using propmed.rel = "lm" in the taxa.compare function (or fitting the model in GAMLSS assuming a different distribution for the response)?
Thanks in advance for any thoughts on the matter!
Nick