Minimum entropy decomposition: unsupervised oligotyping for sensitive partitioning of high-throughput marker gene sequences.

ABSTRACT: Molecular microbial ecology investigations often employ large marker gene datasets, for example, ribosomal RNAs, to represent the occurrence of single-cell genomes in microbial communities. Massively parallel DNA sequencing technologies enable extensive surveys of marker gene libraries that sometimes include nearly identical sequences. Computational approaches that rely on pairwise sequence alignments for similarity assessment and de novo clustering with de facto similarity thresholds to partition high-throughput sequencing datasets constrain fine-scale resolution descriptions of microbial communities. Minimum Entropy Decomposition (MED) provides a computationally efficient means to partition marker gene datasets into 'MED nodes', which represent homogeneous operational taxonomic units. By

SUBMITTER: Eren AM 

PROVIDER: S-EPMC4817710 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature