How BugSeq’s metagenomic classification works¶

BugSeq’s metagenomic classification leverages multiple algorithms to yield optimal results. Results from each algorithm are combined to leverage the strength of each algorithm. The peer-reviewed descriptions of algorithms are found below:

• BugSplit: BugSplit performs especially well on large datasets that can be assembled into contiguous genomes, but also performs well on fragmented assemblies.
• Original BugSeq: Our original algorithm aligns reads to a reference database and refines alignment using a Bayesian statistical framework. While originally designed for ONT data, it was subsequently expanded and validated across sequencing platforms. The Original BugSeq algorithm performs especially well when there are fewer reads in the input data such that they can’t be assembled.

Interpreting metagenomic classification outputs¶

Types of output files¶

BugSeq outputs several files to help our users interpret their metagenomics data. Below is a summary of key outputs that we provide to help you interpret your data:

• Per-Sample Reports: For each sample submitted in a given analysis, BugSeq generates a per-sample HTML and PDF report that provides metagenomic classification results and statistics, antimicrobial resistance prediction, plasmid detection, and quality control statistics.
• Metagenomic Classification Interactive Summary: For each analysis, an interactive Krona-formatted output that displays the number of reads assigned to each taxonomic rank. Double-clicking segments of each plot enables users to subset the data to display only reads assigned to the selected rank and below.
• Metagenomic Classification CSV: For each sample submitted in a given analysis, BugSeq generates a CSV file outlining the classification result and taxonomic rank for each read in a given sample, as well as whether the classification was based on the assembly, or read-based classifier.
• Kraken-formatted Reports: For each sample submitted in a given analysis, BugSeq generates Kraken-formatted reports that outline the taxonomic hierarchy of all reads in a given sample.

See the Per-Sample Reports and Metagenomic Classification Reports pages for more details on specific report interpretation.