metaDprof: An Informative Approach on
Differential Abundance Analysis for Time-course Metagenomic
Sequencing Count Data
We propose a
spline-based statistical approach, metaDprof, to
detect metagenomic features differentially abundant
between biological/medical conditions. It consists two stages: 1) global
detection of features and 2) time interval detection of significant features.
This approach allows heterogeneous error/noise for different biological/medical
conditions and no prior information is needed for the time interval detection.
Even more, this method relies on sound statistical support for both detections.
Download R code.
Return to the page of An lab software: http://cals.arizona.edu/~anling/sbg/software.htm