TaxMapper

TaxMapper maps NGS metatranscriptomic reads to a curated microeukaryotic reference database to provide reliable taxonomic assignments for microeukaryote community analysis.

Key Features:

• Annotated Microeukaryotic Reference Database: Uses a curated database assembled from references selected from the National Center for Biotechnology Information (NCBI) and the Marine Microbial Eukaryote Transcriptome Sequencing Project, comprising 142 references representing main lineages within each of the seven eukaryotic supergroups with predominantly complete transcriptomes or genomes.
• Reliable Mapping and Filtering: Maps sequencing reads against the annotated reference and applies a classifier-based filtering mechanism trained and tested on sequences from taxa within the database, related taxa, and random sequences to remove unreliable taxonomic assignments.
• Snakemake Workflow Integration: Implemented as a component of a Snakemake metatranscriptomic workflow that supports quality assessment, functional and taxonomic annotation, and multivariate statistical analysis including integration of environmental data.
• Improved True Positive Rate: Demonstrates an increase in the number of true positive taxonomic assignments compared to standard approaches.

Scientific Applications:

• Environmental metatranscriptomics: Resolve microeukaryote community composition and transcriptional activity from NGS metatranscriptome datasets.
• Eukaryotic community taxonomic profiling: Provide higher-confidence taxonomic assignments for microeukaryotes in contexts with low or fragmented reference coverage.
• Multivariate ecological analysis: Enable integration of taxonomic and functional annotations with environmental data for multivariate statistical analyses of microbial ecosystems.

Methodology:

Mapping of NGS reads to an annotated microeukaryotic reference database and classifier-based filtering trained/tested on database taxa, related taxa, and random sequences, implemented within a Snakemake workflow that includes quality assessment, functional and taxonomic annotation, and multivariate statistical analysis with environmental data integration.