Quantifying and comparing bacterial growth dynamics in multiple metagenomic samples

Accurately quantifying microbial growth dynamics for species without complete genome sequences is biologically important but computationally challenging in metagenomics. Here we present DEMIC, a new multi-sample algorithm based on contigs and coverage values, to infer relative distances of contigs from replication origin and to accurately compare bacterial growth rates between samples. We demonstrate robust performances of DEMIC for various sample sizes and assembly qualities using multiple synthetic and real datasets.