Ondov, B. D. | bioRxiv Science

bioRxiv2019

Mash Screen: High-throughput sequence containment estimation for genome discovery

The MinHash algorithm has proven effective for rapidly estimating the resemblance of two genomes or metagenomes. However, this method cannot reliably estimate the containment of a genome within a metagenome. Here we describe an online algorithm capable of measuring the containment of genomes and proteomes within either assembled or unassembled sequencing read sets. We describe several use cases, including contamination screening and retrospective analysis of metagenomes for novel genome discovery. Using this tool, we provide containment estimates for every NCBI RefSeq genome within every SRA metagenome, and demonstrate the identification of a novel polyomavirus species from a public metagenome.

bioinformatics↗

bioRxiv2017

BLAST-based validation of metagenomic sequence assignments

When performing bioforensic casework, it is important to be able to reliably detect the presence of a particular organism in a metagenomic sample, even if the organism is only present in a trace amount. For this task, it is common to use a sequence classification program that determines the taxonomic affiliation of individual sequence reads by comparing them to reference database sequences. As metagenomic data sets often consist of millions or billions of reads that need to be compared to reference databases containing millions of sequences, such sequence classification programs typically use search heuristics and databases with reduced sequence diversity to speed up the analysis, which can lead to incorrect assignments. Thus, in a bioforensic setting where correct assignments are paramount, assignments of interest made by \"first-pass\" classifiers should be confirmed using the most precise methods and comprehensive databases available. In this study we present a O_SCPLOWBLASTC_SCPLOW-based method for validating the assignments made by less precise sequence classification programs, with optimal parameters for filtering of O_SCPLOWBLASTC_SCPLOW results determined via simulation of sequence reads from genomes of interest, and we apply the method to the detection of four pathogenic organisms. The software implementing the method is open source and freely available.

bioinformatics↗