Differential abundance analysis for microbial marker-gene surveys

The metagenomeSeq tool robustly detects the differential abundance of microbes in marker-based microbial surveys by tackling the problems of data sparsity and undersampling common to these data sets. We introduce a methodology to assess differential abundance in sparse high-throughput microbial marker-gene survey data. Our approach, implemented in the metagenomeSeq Bioconductor package, relies on a novel normalization technique and a statistical model that accounts for undersampling—a common feature of large-scale marker-gene studies. Using simulated data and several published microbiota data sets, we show that metagenomeSeq outperforms the tools currently used in this field.