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.
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