I propose an enhancement to the ANCOMBC2 tool to support using taxa as explanatory variables, catering to the substantial interest within the research community in studying the relationship between microbiota and diseases. Particularly, integrating logistic regression would be beneficial, as outcomes in these studies are often binomial (disease vs. control), which necessitates a model that can handle binary outcomes effectively. This feature would allow researchers to use microbial compositions to predict health conditions, thereby expanding ANCOMBC2’s utility in microbiome research and aiding in the exploration of how microbiota may contribute to or indicate disease states. This update would provide significant value in clinical and translational research, where understanding the potential role of microbiota in disease mechanisms is crucial.
Thank you for considering this enhancement to broaden the scope and impact of ANCOMBC2 in microbiome-related health research.
Feature Request
I propose an enhancement to the ANCOMBC2 tool to support using taxa as explanatory variables, catering to the substantial interest within the research community in studying the relationship between microbiota and diseases. Particularly, integrating logistic regression would be beneficial, as outcomes in these studies are often binomial (disease vs. control), which necessitates a model that can handle binary outcomes effectively. This feature would allow researchers to use microbial compositions to predict health conditions, thereby expanding ANCOMBC2’s utility in microbiome research and aiding in the exploration of how microbiota may contribute to or indicate disease states. This update would provide significant value in clinical and translational research, where understanding the potential role of microbiota in disease mechanisms is crucial.
Thank you for considering this enhancement to broaden the scope and impact of ANCOMBC2 in microbiome-related health research.