SprayNPray

SprayNPray performs rapid taxonomic profiling of genome and metagenome contigs from shotgun sequencing datasets to classify contigs and support detection of contaminants and horizontal gene transfer.

Key Features:

• Contig-level sequence and coverage metrics: Profiles contigs using gene density, read coverage, GC content, tetranucleotide frequency, and codon-usage bias.
• Reference-homology searches: Identifies closest homologs for contigs from user-specified reference databases.
• Genome and metagenome compatibility: Applies to contigs derived from whole-genome sequencing of cultured isolates, individual eukaryotes, and metagenome-assembled genomes.
• Contaminant and HGT identification: Enables identification of contigs from putative contaminants and detection of possible horizontal gene transfer events, including bacteria detected in eukaryotic assemblies and vice versa.

Scientific Applications:

• Broad-level overviews: Produces preliminary taxonomic profiles of shotgun sequencing datasets for high-level community or assembly assessment.
• Supplement to classification and binning: Provides taxonomic and metric information to complement other taxonomic classification or binning software.
• Spot-checking MAGs: Assesses metagenome-assembled genomes for taxonomic consistency and anomalous contigs.
• Contaminant removal in isolate assemblies: Identifies contigs likely originating from contaminants for removal from isolate genome assemblies.
• Cross-domain detection: Detects bacterial contigs in eukaryotic assemblies and eukaryotic contigs in bacterial assemblies.
• Horizontal gene transfer detection: Flags contigs with taxonomic signals indicative of possible horizontal gene transfer events.
• Cultured isolate analysis: Supports taxonomic profiling of whole-genome sequencing data from cultured microbial isolates and individual eukaryotes.
• Metagenomic community analysis: Supports examination of complex microbial communities via metagenomic contig profiling.

Methodology:

Profiles contigs by identifying closest homologs from user-specified reference databases and computing gene density, read coverage, GC content, tetranucleotide frequency, and codon-usage bias.