DSM

DSM performs content-based exploration and retrieval of whole metagenome sequencing samples by extracting informative sequence k-mers to compare microbial community composition in studies such as the Human Microbiome Project and investigations of the human intestinal tract.

Key Features:

• Content-Based Exploration: Enables comparison and retrieval of metagenomic samples based on shared sequence content and k-mer profiles.
• Distributed String Mining Framework: Implements a distributed string mining approach to process multiple metagenomic samples concurrently.
• Informative k-mer Extraction: Extracts informative sequence k-mers from metagenomic datasets for downstream comparison.
• Measurement of Dissimilarity: Quantifies dissimilarities between samples using the extracted k-mer sets.
• Scalable Processing of Whole Metagenome Shotgun Sequencing: Supports efficient handling of large-scale whole metagenome shotgun sequencing data through distributed computation.

Scientific Applications:

• Comparative microbial community analysis: Facilitates comparisons of microbial communities across conditions and environments, including human gut metagenome studies.
• Disease-associated microbiome identification: Supports enrichment analyses that detect diseased gut samples when queried with diseased profiles, aiding identification of disease-associated microbiomes.
• Body-site differentiation: Distinguishes microbial communities from different body sites with high accuracy despite operating as an unsupervised method.

Methodology:

DSM uses a distributed string mining framework to extract informative sequence k-mers from whole metagenome shotgun sequencing samples and computes sample dissimilarities based on the extracted k-mers; its performance has been evaluated on human gut metagenome datasets and Human Microbiome Project samples.