miComplete

miComplete evaluates completeness and redundancy of metagenome-assembled genomes (MAGs) and single-cell amplified genomes (SAGs) by weighting conserved marker genes according to their median inter-marker distances in complete reference genomes.

Key Features:

• Weighted Quality Evaluation: Normalizes presence or absence of conserved gene markers using median distances to adjacent markers computed from complete reference genomes.
• Marker-based Completeness and Redundancy Estimation: Estimates genome completeness and redundancy from conserved gene markers rather than raw marker counts.
• Spatial Distribution Bias Reduction: Accounts for spatial distribution of markers to reduce biases from clustered markers such as ribosomal protein operons.
• Implementation: Implemented in Python 3 and released under the GPLv3 license.

Scientific Applications:

• MAG Quality Assessment: Assesses completeness and redundancy of metagenome-assembled genomes (MAGs).
• SAG Quality Assessment: Assesses completeness and redundancy of single-cell amplified genomes (SAGs).
• Microbial Diversity and Evolutionary Analyses: Supports studies of microbial diversity and evolutionary relationships by providing more accurate genome-quality estimates.

Methodology:

miComplete computes median distances between conserved marker genes in complete reference genomes and uses those distances to weight and normalize marker presence/absence when estimating genome completeness and redundancy.