Hello, Yang Cao! Thanks for the excellent package!
Background:
I run differential abundance analysis/biomarker identification with microbiomeMarker, and the program running smoothly. I have tried every differential abundance analysis methods (simple statistical, RNA-seq based, metagenome based, and supervised learning method) with each transformation and normalization methods.
My question is:
The markers found by different analysis methods are not completely consistent, even the markers found by different transformation and normalization methods of the same method could be different. Which analysis method and transformation/normalization method are more reliable? How should we choose the varied markers identified by different methods, such as those found consistently by several methods, or combining the biological significance of the research topic?
Sorry, my question is a little long.
Thanks for your help!
Hello, Yang Cao! Thanks for the excellent package!
Background: I run differential abundance analysis/biomarker identification with microbiomeMarker, and the program running smoothly. I have tried every differential abundance analysis methods (simple statistical, RNA-seq based, metagenome based, and supervised learning method) with each transformation and normalization methods.
My question is: The markers found by different analysis methods are not completely consistent, even the markers found by different transformation and normalization methods of the same method could be different. Which analysis method and transformation/normalization method are more reliable? How should we choose the varied markers identified by different methods, such as those found consistently by several methods, or combining the biological significance of the research topic?
Sorry, my question is a little long. Thanks for your help!