MetaErg

MetaErg annotates and visualizes metagenomic and metaproteomic datasets to provide gene-level taxonomic and functional inferences.

Key Features:

• Dataset scope: Supports annotation of metagenomic and metaproteomic datasets containing sequences from multiple domains of life.
• Feature prediction: Predicts biological features including genes, CRISPR arrays, and non-coding RNA genes such as tRNA and rRNA.
• Functional annotation: Performs functional annotation using Hidden Markov Model (HMM) searches.
• Sequence similarity searches: Executes sequence alignment searches using BLAST and DIAMOND.
• Taxonomic classification: Assigns taxonomic classifications at the gene level and integrates these with functional inferences.
• Low-similarity inference: Provides functional predictions for genes with low sequence similarity to reference genes.
• Quantitative activity mapping: Visualizes gene and pathway activity using sequencing coverage and proteomics spectral counts.
• Assembly/binning artifact awareness: Accounts for issues arising from imperfect assembly and binning, including artifactual hybrid contigs or genomes.
• Integrated pipeline: Integrates feature prediction, similarity searches, taxonomic classification, and functional annotation in an automated workflow.

Scientific Applications:

• Metagenomic annotation: Annotates genes and predicts functions across complex microbial communities spanning multiple domains of life.
• Metaproteomic analysis: Maps proteomics spectral counts to genes and pathways to assess protein-level activity.
• Taxonomic profiling: Quantitatively profiles taxonomic composition across samples at the gene level.
• Functional inference of novel genes: Infers functions for genes from understudied lineages or with low similarity to known references.
• Assembly and binning assessment: Detects and helps interpret artifacts from imperfect assembly or binning such as hybrid contigs or genomes.

Methodology:

Performs feature prediction (genes, CRISPR arrays, tRNA, rRNA), HMM-based functional annotation, BLAST and DIAMOND sequence searches, gene-level taxonomic classification and functional inference, and visualizes gene/pathway activity using sequencing coverage and proteomics spectral counts.