Motivation: Metagenomics involves sampling and studying the genetic materials in microbial communities. Several statistical methods have been proposed for comparative analysis of microbial community compositions. Most of the methods are based on the estimated abundances of taxonomic units or functional groups from metagenomic samples. However, such estimated abundances might deviate from the true abundances in habitats due to sampling biases and other systematic artifacts in metagenomic data processing.
Results: We developed the MetaRank scheme to convert abundances into ranks. MetaRank employs a series of statistical hypothesis tests to compare abundances within a microbial community and determine their ranks. We applied MetaRank to synthetic samples and real metagenomes. The results confirm that MetaRank can reduce the effects of sampling biases and clarify the characteristics of metagenomes in comparative studies of microbial communities. Therefore, MetaRank provides a useful rank-based approach to analyzing microbiomes.
Supplementary Information: Supplementary data are available at Bioinformatics online.